From d054f5a42053cf5054d3cfd94771b0e7c095f413 Mon Sep 17 00:00:00 2001 From: AG Damsbo Date: Fri, 14 Apr 2023 11:47:23 +0200 Subject: [PATCH] minor --- NAMESPACE | 1 + R/sysdata.rda | Bin 295 -> 291 bytes data-raw/redcapcast_meta.R | 2 +- data/redcapcast_meta.rda | Bin 1478 -> 1498 bytes docs/articles/Introduction.html | 419 +++++++++++++------------- docs/pkgdown.yml | 2 +- docs/reference/clean_redcap_name.html | 101 +++++++ docs/reference/index.html | 5 + docs/reference/redcapcast_data.html | 4 +- docs/search.json | 2 +- docs/sitemap.xml | 3 + man/clean_redcap_name.Rd | 19 ++ man/redcapcast_data.Rd | 4 +- tests/testthat/helper-paths.R | 2 + tests/testthat/test-csv-exports.R | 4 +- vignettes/Introduction.Rmd | 10 +- 16 files changed, 353 insertions(+), 225 deletions(-) create mode 100644 docs/reference/clean_redcap_name.html create mode 100644 man/clean_redcap_name.Rd diff --git a/NAMESPACE b/NAMESPACE index 1137ebc..6ea6314 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,6 +1,7 @@ # Generated by roxygen2: do not edit by hand export(REDCap_split) +export(clean_redcap_name) export(focused_metadata) export(match_fields_to_form) export(read_redcap_tables) diff --git a/R/sysdata.rda b/R/sysdata.rda index 0299f29acc10d71483fb818db38ea7f631055462..cb869c807e17f73f29c1727e2ea7084776bdf301 100644 GIT binary patch literal 291 zcmV+;0o?vVT4*^jL0KkKS&c->Y5)LT|A72C_yGVA5C8-K5J120|KI=tFaY|hhJ+(V zr-CCvrh`Dyh+|C#fEhFfMw%F!Fk(~DqzR&AdPWmW4M(KSH<$;yHlR7dAk%gc-!~H8 z&zBxmTDs2dUc`XFkV8W=Lm&uYdH_K%*6yC-`6aSRpiHU7OKsNFttUG`_fhfW^_Ufg zq$5ks=yJ*xZE%h#G6ItUCd|W=DlCV_f>UC{TLLb6BZ@Kcz^lg5nyC&E;>ndu_?z2C zdmNox1{mP@)Jixf(HUg)6E&xJ)`(yoKZk1$9!*aW(i&vbO+8Q57>y4A9TBww&Itx{-{(C# zxR<*>I61;c!Ey~Db0DD!G$W72+>uTcBr*}%z`*O7dP@KR diff --git a/data-raw/redcapcast_meta.R b/data-raw/redcapcast_meta.R index fe9f3f6..23a7dba 100644 --- a/data-raw/redcapcast_meta.R +++ b/data-raw/redcapcast_meta.R @@ -1,5 +1,5 @@ ## code to prepare `redcapcast_meta` dataset goes here -redcapcast_meta <- REDCapR::redcap_metadata_read(redcap_uri = uri, +redcapcast_meta <- REDCapR::redcap_metadata_read(redcap_uri = keyring::key_get("DB_URI"), token = keyring::key_get("cast_api") )$data diff --git a/data/redcapcast_meta.rda b/data/redcapcast_meta.rda index 35cce09bb5a285dc39077ca0ad2da9e3f12c5268..36c58c9cf3a098f9a45b744b4ce73193957a62a5 100644 GIT binary patch delta 1483 zcmV;+1vL7`3)%|~LRx4!F+o`-Q(2gS-{g@FBY*xZ$2%RdUAfm?rn=W@ZW2WTGH7ag zr|BMq%6guSAk$4W&}e7@pfuAXMnJ^KGDd{NQ`$_XDWht7Ce%GZ4FEI%02&Pd4FQOg zOi8MKno#zndYS>D>HrM~p#W__0009)!J|fjpwJmH0g<7Q02*nK006-N1W6GiO-6$$ zd9I%@mW^``NW^=43(J&X;K*fo}k zY+++}mM$b)HLBkfELIx@%p*DyPQWCLQBbHf5=Nki1>hn+j&ZqU4NTO6?LZH(eBQh= zmlgitffhzFf-(RSn$zy%Sdlg(P!B-eB@Yh>h&@PGW_ zl2EUYmC&i0ld?6&un&JIfOt03hyp;GIVh}6$w3~CTKyrl*tk*cS!ufSgcao)~xG<;QU zt(X|ea_2VsH?r8nK2DBX-vR^(1b-NiWFSC*a&fqFv{n_EMyiU&z$LkUB> zxDbJ}5(GG-ca1Cvd@V^P}?B_b>n(7)Rm;_reK^#|b$yOtI zA%eW5h)07Vi~ttKA`=s13bunvZj+#qtkQzef#YqWp_LP)C>FdjJsoDOGq{0AE3*b1 z-EgaXlMX4t$>K~4;|Ky(#9LO)2SZ&<(1+3j7#KON#*cf-gAsd$yMI(7SV?j=fr5#! ztx%zJjEUSMyn&04?O4eU8f+?;sNVCS3?f|XvE{&Va0UP!t=J6*5+VxXD9Fe*)+=Zs zP>8o*d<_&k`_zqA&TLp&vKPsVf+@PHyf8BfZ!(uItjZmpEXrG#1qUNtBpApTv8mq{ zJJ1d$7{gWf@a(q^QGX*pKM2BBS(rjt6-`=Oyj^aFq!Tr@Yc@nnr@T6|z9$ApnG3B@M;&M`>}v9s!)D zK)U+!rYmEclWx_etXm7$T#A$|K$!`c7fr_qFvWU}b*HaXMt@BC2?u9#sD#TX9cQKW zTMRLav0xHHl-3wgKy%@GDz&910TxqCnj%irLS>4St9OY(mmh;BZsROgWRQ(wL>j`L zO_0%fXxWSkc~DmSuZ}%g5t(_*T1hH9`UGrH)`bL_rwuYKf&FwTHK8xUoNANK8QQ@&I7Pk~-yVOKO5^yfPs)5i``( z@ijJuJrl(qqeCMT)HDDz2AKh%2dEN+38PaIWYIEtCN(l>05k@G000^Q8Uqx{WNMpK z{3#!$0BFedGyr;;4Kg$vApigX0Th(dG&Cj#ngE`Y38MfF01(7r35lakpa~Kp8mE$a zkAFn;)YH`Tn2iAS00SWMfb>8-qtXGR)b)XiAy#q)3Nk@y zLTQgTbo&xvTF@Xu#4y7GEr1RbWBc2X+BDjRE3WT%bXc*2j7LnyOrY`>Op-|`S%1~P zQv8F6KN#<&<)?!oL?Jq~BPhrN;=nj(hSLWGfuA~~6pSaEK0GxqZ*~Jf4a)FxdbaBOzd5GHBs>DSBfI|wEMQCu(QU+s8VWoK>O%1gX3lA4DIs~c7 ze6@pGC3jJUEzFs(JQ*sHMf%%yPJeU^7%&)`7@HU{U|gnQdjwGyL@Ly6)YHGTfjcx3 zXcDBG3lvGB<_K6njH;Fiy8fQdTgR->ob9^%u8OQ72+C%Hm6zWvOIo$5Vy%rhrZc3i zM1f}I`~<*g&p{+L(uScXCN`La!D^5YK+Zrr^AMnrGC;#rPGm_)30qiT(|aOUe*`Jdeq-QM@+EM=!SoUPs6_;~qrh}{nEe?_Oi%@XEO zzsAx%!eRAda&de7G*a=@5(Nsk^O6j=QUHO5GaDPl5P?Ai2vH6LW^InM+{?V;k5y1* zzR^wloEmecs5aG7lnja*AAg~?9*}t<+4;ZMdJ1br8jtd8q$84G0UE<$kvi=3$9SNc zqC{!p)G#6OK_YN9z`I&G>()+EMrJ5j5Qxgck*2F6;r3$56@@X&S_l_G@X9h}>j;RC zlETw}76pL#sGuOv5JYohVA!(ZPH-woB?mhq#xX~UGe&`Coup5LH-E;~-bhR?T2wQK z56T)Tm?I}KVf>;3)WhZLOWjn#h@+ErlX2$0kdoQ<$j+EmRHVz=b&k27>&aA1yDtD| zy*M}TomQXB`l`DHWuh7vCOr{BAWx+oEl!Nf<@sbY;B$d&n#mypNHKw-n-#Yp7*rIu z6EHVQF zMHpsbQ4~sT5sWR@dxi_MisKmK#<J!!(XuvTNJc714WQG~w*0e}4VfNO zi3O;kJe1KX7+cnDqDe5|z9K>#k|+wmNh+y?8SrSPn2eV4U$@-37eRBN5{Y4}E%_mS zY)J-1o=#lb!;LQg zYztylVoE4srDzg;mLo(++T&5k!syB*Mj}Sn34FO}@E}D>(CseXwN@wq^m>E*#*hgE RsG<+JyOJrwgoO3M@nEP-jurp_ diff --git a/docs/articles/Introduction.html b/docs/articles/Introduction.html index 881bd31..c4dd0ef 100644 --- a/docs/articles/Introduction.html +++ b/docs/articles/Introduction.html @@ -91,12 +91,12 @@ demonstration of the functions.

 redcapcast_data |> gt::gt()
-
+
@@ -518,14 +518,14 @@ demonstration of the functions.

hypertension diabetes region - base_complete + baseline_data_start_complete mrs_assessed mrs_date mrs_score mrs_complete event_date event_type - event_complete + new_event_complete @@ -543,14 +543,14 @@ demonstration of the functions.

No Yes East -Incomplete +Incomplete Yes 2023-03-13 1 Incomplete NA NA -NA +NA 2 @@ -567,14 +567,14 @@ demonstration of the functions.

No No South -Incomplete +Incomplete Yes 2023-03-07 1 Incomplete NA NA -NA +NA 2 @@ -591,19 +591,19 @@ demonstration of the functions.

NA NA NA -NA +NA Yes 2023-03-09 3 Incomplete NA NA -NA +NA 2 follow1 -Event +New Event (?) 1 NA NA @@ -615,14 +615,14 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2023-03-13 TIA -Incomplete +Incomplete 3 @@ -639,14 +639,14 @@ demonstration of the functions.

Yes Yes North -Incomplete +Incomplete NA NA NA Incomplete NA NA -NA +NA 3 @@ -663,14 +663,14 @@ demonstration of the functions.

NA NA NA -NA +NA Yes 2022-08-16 2 Incomplete NA NA -NA +NA 3 @@ -687,19 +687,19 @@ demonstration of the functions.

NA NA NA -NA +NA Yes 2023-03-13 1 Incomplete NA NA -NA +NA 3 follow1 -Event +New Event (?) 1 NA NA @@ -711,19 +711,19 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2022-11-08 AIS -Incomplete +Incomplete 3 follow1 -Event +New Event (?) 2 NA NA @@ -735,19 +735,19 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2022-12-14 ICH -Incomplete +Incomplete 3 follow2 -Event +New Event (?) 1 NA NA @@ -759,19 +759,19 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2023-02-06 ICH -Incomplete +Incomplete 3 follow2 -Event +New Event (?) 2 NA NA @@ -783,19 +783,19 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2023-03-13 TIA -Incomplete +Incomplete 3 follow2 -Event +New Event (?) 3 NA NA @@ -807,14 +807,14 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2023-02-28 AIS -Incomplete +Incomplete 4 @@ -831,14 +831,14 @@ demonstration of the functions.

NA NA NA -Incomplete +Incomplete NA NA NA Incomplete NA NA -NA +NA 4 @@ -855,19 +855,19 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA Incomplete NA NA -NA +NA 4 follow2 -Event +New Event (?) 1 NA NA @@ -879,19 +879,19 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2023-01-02 AIS -Complete +Complete 4 follow2 -Event +New Event (?) 2 NA NA @@ -903,19 +903,19 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2023-02-06 ICH -Incomplete +Incomplete 4 follow2 -Event +New Event (?) 3 NA NA @@ -927,14 +927,14 @@ demonstration of the functions.

NA NA NA -NA +NA NA NA NA NA 2023-03-05 Unknown -Complete +Complete 5 @@ -951,26 +951,26 @@ demonstration of the functions.

Yes Yes East -Complete +Complete NA NA NA Incomplete NA NA -NA +NA 
 redcapcast_meta |> gt::gt()
-
+
@@ -1400,7 +1400,7 @@ demonstration of the functions.

record_id -base +baseline_data_start NA text ID @@ -1420,7 +1420,7 @@ demonstration of the functions.

cpr -base +baseline_data_start NA text CPR (Danish civil registration number) @@ -1440,7 +1440,7 @@ demonstration of the functions.

inclusion -base +baseline_data_start NA text Inclusion date @@ -1460,7 +1460,7 @@ demonstration of the functions.

dob -base +baseline_data_start NA text Date of birth (From CPR) @@ -1480,7 +1480,7 @@ demonstration of the functions.

age -base +baseline_data_start NA calc Age @@ -1501,7 +1501,7 @@ Note: Apparently, the build in datediff() function does not handle counting whol age_integer -base +baseline_data_start NA calc Age integer @@ -1522,7 +1522,7 @@ Note: as opposed to the build in datediff() this handles counting years as integ sex -base +baseline_data_start NA text Legal sex @@ -1542,7 +1542,7 @@ Note: as opposed to the build in datediff() this handles counting years as integ cohabitation -base +baseline_data_start History and social radio Cohabitation @@ -1562,7 +1562,7 @@ Note: as opposed to the build in datediff() this handles counting years as integ hypertension -base +baseline_data_start NA radio Hypertension @@ -1582,7 +1582,7 @@ Note: as opposed to the build in datediff() this handles counting years as integ diabetes -base +baseline_data_start NA radio Diabetes @@ -1602,7 +1602,7 @@ Note: as opposed to the build in datediff() this handles counting years as integ region -base +baseline_data_start Area dropdown Region @@ -1682,7 +1682,7 @@ Note: as opposed to the build in datediff() this handles counting years as integ event_date -event +new_event NA text Date of event @@ -1702,7 +1702,7 @@ Note: as opposed to the build in datediff() this handles counting years as integ event_type -event +new_event NA radio Neurovascular event @@ -1725,89 +1725,88 @@ Note: as opposed to the build in datediff() this handles counting years as integ 
 list <-
-  REDCapCAST::REDCap_split(records = redcapcast_data,
+  REDCap_split(records = redcapcast_data,
                            metadata = redcapcast_meta,
                            forms = "repeating")
 str(list)
 #> List of 2
-#>  $      :'data.frame':   9 obs. of  20 variables:
-#>   ..$ record_id        : num [1:9] 1 2 2 3 3 3 4 4 5
-#>   ..$ redcap_event_name: chr [1:9] "inclusion" "inclusion" "follow1" "inclusion" ...
-#>   ..$ cpr              : chr [1:9] "1203401OB4" "0102342303" NA "2301569823" ...
-#>   ..$ inclusion        : Date[1:9], format: "2023-03-13" "2023-03-01" ...
-#>   ..$ dob              : Date[1:9], format: "1940-03-12" "1934-02-01" ...
-#>   ..$ age              : num [1:9] 83 89.1 NA 66.1 NA ...
-#>   ..$ age_integer      : num [1:9] 83 89 NA 66 NA NA 117 NA 126
-#>   ..$ sex              : chr [1:9] "female" "male" NA "male" ...
-#>   ..$ cohabitation     : chr [1:9] "Yes" "Yes" NA "No" ...
-#>   ..$ hypertension     : chr [1:9] "No" "No" NA "Yes" ...
-#>   ..$ diabetes         : chr [1:9] "Yes" "No" NA "Yes" ...
-#>   ..$ region           : chr [1:9] "East" "South" NA "North" ...
-#>   ..$ base_complete    : chr [1:9] "Incomplete" "Incomplete" NA "Incomplete" ...
-#>   ..$ mrs_assessed     : chr [1:9] "Yes" "Yes" "Yes" NA ...
-#>   ..$ mrs_date         : Date[1:9], format: "2023-03-13" "2023-03-07" ...
-#>   ..$ mrs_score        : num [1:9] 1 1 3 NA 2 1 NA NA NA
-#>   ..$ mrs_complete     : chr [1:9] "Incomplete" "Incomplete" "Incomplete" "Incomplete" ...
-#>   ..$ event_date       : Date[1:9], format: NA NA ...
-#>   ..$ event_type       : chr [1:9] NA NA NA NA ...
-#>   ..$ event_complete   : chr [1:9] NA NA NA NA ...
-#>  $ Event:'data.frame':   9 obs. of  4 variables:
+#>  $          :'data.frame':   9 obs. of  17 variables:
+#>   ..$ record_id                   : num [1:9] 1 2 2 3 3 3 4 4 5
+#>   ..$ redcap_event_name           : chr [1:9] "inclusion" "inclusion" "follow1" "inclusion" ...
+#>   ..$ cpr                         : chr [1:9] "1203401OB4" "0102342303" NA "2301569823" ...
+#>   ..$ inclusion                   : Date[1:9], format: "2023-03-13" "2023-03-01" ...
+#>   ..$ dob                         : Date[1:9], format: "1940-03-12" "1934-02-01" ...
+#>   ..$ age                         : num [1:9] 83 89.1 NA 66.1 NA ...
+#>   ..$ age_integer                 : num [1:9] 83 89 NA 66 NA NA 117 NA 126
+#>   ..$ sex                         : chr [1:9] "female" "male" NA "male" ...
+#>   ..$ cohabitation                : chr [1:9] "Yes" "Yes" NA "No" ...
+#>   ..$ hypertension                : chr [1:9] "No" "No" NA "Yes" ...
+#>   ..$ diabetes                    : chr [1:9] "Yes" "No" NA "Yes" ...
+#>   ..$ region                      : chr [1:9] "East" "South" NA "North" ...
+#>   ..$ baseline_data_start_complete: chr [1:9] "Incomplete" "Incomplete" NA "Incomplete" ...
+#>   ..$ mrs_assessed                : chr [1:9] "Yes" "Yes" "Yes" NA ...
+#>   ..$ mrs_date                    : Date[1:9], format: "2023-03-13" "2023-03-07" ...
+#>   ..$ mrs_score                   : num [1:9] 1 1 3 NA 2 1 NA NA NA
+#>   ..$ mrs_complete                : chr [1:9] "Incomplete" "Incomplete" "Incomplete" "Incomplete" ...
+#>  $ new_event:'data.frame':   9 obs. of  7 variables:
 #>   ..$ record_id               : num [1:9] 2 3 3 3 3 3 4 4 4
 #>   ..$ redcap_event_name       : chr [1:9] "follow1" "follow1" "follow1" "follow2" ...
-#>   ..$ redcap_repeat_instrument: chr [1:9] "Event" "Event" "Event" "Event" ...
-#>   ..$ redcap_repeat_instance  : num [1:9] 1 1 2 1 2 3 1 2 3
+#> ..$ redcap_repeat_instrument: chr [1:9] "new_event" "new_event" "new_event" "new_event" ... +#> ..$ redcap_repeat_instance : num [1:9] 1 1 2 1 2 3 1 2 3 +#> ..$ event_date : Date[1:9], format: "2023-03-13" "2022-11-08" ... +#> ..$ event_type : chr [1:9] "TIA" "AIS" "ICH" "ICH" ... +#> ..$ new_event_complete : chr [1:9] "Incomplete" "Incomplete" "Incomplete" "Incomplete" ...
 list <-
-  REDCapCAST::REDCap_split(records = redcapcast_data,
+  REDCap_split(records = redcapcast_data,
                            metadata = redcapcast_meta,
                            forms = "all")
 str(list)
-#> List of 4
-#>  $ base :'data.frame':   9 obs. of  13 variables:
-#>   ..$ record_id        : num [1:9] 1 2 2 3 3 3 4 4 5
-#>   ..$ redcap_event_name: chr [1:9] "inclusion" "inclusion" "follow1" "inclusion" ...
-#>   ..$ cpr              : chr [1:9] "1203401OB4" "0102342303" NA "2301569823" ...
-#>   ..$ inclusion        : Date[1:9], format: "2023-03-13" "2023-03-01" ...
-#>   ..$ dob              : Date[1:9], format: "1940-03-12" "1934-02-01" ...
-#>   ..$ age              : num [1:9] 83 89.1 NA 66.1 NA ...
-#>   ..$ age_integer      : num [1:9] 83 89 NA 66 NA NA 117 NA 126
-#>   ..$ sex              : chr [1:9] "female" "male" NA "male" ...
-#>   ..$ cohabitation     : chr [1:9] "Yes" "Yes" NA "No" ...
-#>   ..$ hypertension     : chr [1:9] "No" "No" NA "Yes" ...
-#>   ..$ diabetes         : chr [1:9] "Yes" "No" NA "Yes" ...
-#>   ..$ region           : chr [1:9] "East" "South" NA "North" ...
-#>   ..$ base_complete    : chr [1:9] "Incomplete" "Incomplete" NA "Incomplete" ...
-#>  $ mrs  :'data.frame':   9 obs. of  6 variables:
+#> List of 3
+#>  $ baseline_data_start:'data.frame': 9 obs. of  13 variables:
+#>   ..$ record_id                   : num [1:9] 1 2 2 3 3 3 4 4 5
+#>   ..$ redcap_event_name           : chr [1:9] "inclusion" "inclusion" "follow1" "inclusion" ...
+#>   ..$ cpr                         : chr [1:9] "1203401OB4" "0102342303" NA "2301569823" ...
+#>   ..$ inclusion                   : Date[1:9], format: "2023-03-13" "2023-03-01" ...
+#>   ..$ dob                         : Date[1:9], format: "1940-03-12" "1934-02-01" ...
+#>   ..$ age                         : num [1:9] 83 89.1 NA 66.1 NA ...
+#>   ..$ age_integer                 : num [1:9] 83 89 NA 66 NA NA 117 NA 126
+#>   ..$ sex                         : chr [1:9] "female" "male" NA "male" ...
+#>   ..$ cohabitation                : chr [1:9] "Yes" "Yes" NA "No" ...
+#>   ..$ hypertension                : chr [1:9] "No" "No" NA "Yes" ...
+#>   ..$ diabetes                    : chr [1:9] "Yes" "No" NA "Yes" ...
+#>   ..$ region                      : chr [1:9] "East" "South" NA "North" ...
+#>   ..$ baseline_data_start_complete: chr [1:9] "Incomplete" "Incomplete" NA "Incomplete" ...
+#>  $ mrs                :'data.frame': 9 obs. of  6 variables:
 #>   ..$ record_id        : num [1:9] 1 2 2 3 3 3 4 4 5
 #>   ..$ redcap_event_name: chr [1:9] "inclusion" "inclusion" "follow1" "inclusion" ...
 #>   ..$ mrs_assessed     : chr [1:9] "Yes" "Yes" "Yes" NA ...
 #>   ..$ mrs_date         : Date[1:9], format: "2023-03-13" "2023-03-07" ...
 #>   ..$ mrs_score        : num [1:9] 1 1 3 NA 2 1 NA NA NA
 #>   ..$ mrs_complete     : chr [1:9] "Incomplete" "Incomplete" "Incomplete" "Incomplete" ...
-#>  $ event:'data.frame':   9 obs. of  5 variables:
-#>   ..$ record_id        : num [1:9] 1 2 2 3 3 3 4 4 5
-#>   ..$ redcap_event_name: chr [1:9] "inclusion" "inclusion" "follow1" "inclusion" ...
-#>   ..$ event_date       : Date[1:9], format: NA NA ...
-#>   ..$ event_type       : chr [1:9] NA NA NA NA ...
-#>   ..$ event_complete   : chr [1:9] NA NA NA NA ...
-#>  $ Event:'data.frame':   9 obs. of  4 variables:
+#>  $ new_event          :'data.frame': 9 obs. of  7 variables:
 #>   ..$ record_id               : num [1:9] 2 3 3 3 3 3 4 4 4
 #>   ..$ redcap_event_name       : chr [1:9] "follow1" "follow1" "follow1" "follow2" ...
-#>   ..$ redcap_repeat_instrument: chr [1:9] "Event" "Event" "Event" "Event" ...
-#>   ..$ redcap_repeat_instance  : num [1:9] 1 1 2 1 2 3 1 2 3
+#> ..$ redcap_repeat_instrument: chr [1:9] "new_event" "new_event" "new_event" "new_event" ... +#> ..$ redcap_repeat_instance : num [1:9] 1 1 2 1 2 3 1 2 3 +#> ..$ event_date : Date[1:9], format: "2023-03-13" "2022-11-08" ... +#> ..$ event_type : chr [1:9] "TIA" "AIS" "ICH" "ICH" ... +#> ..$ new_event_complete : chr [1:9] "Incomplete" "Incomplete" "Incomplete" "Incomplete" ...

Reading data from REDCap

This function wraps all the above demonstrated function to get the dataset, the metadata, apply the REDCap_splitfunction and -then a bit of cleaning.

+then a bit of cleaning. It just cuts outs all the steps for an easier +approach.

The function works very similar to the -REDCapR::redcap_read().

+REDCapR::redcap_read() in allowing to specify fields, +events and forms for export instead of exporting the whole database and +filtering afterwards. I believe this is a better and safer, focused +approach.

-# read_redcap_tables(uri = "YOUR URI", token = "YOUR TOKEN")
-
-# ds <- read_redcap_tables(uri = key_get("DB_URI"), token = key_get("cast_api"))
+# read_redcap_tables(uri = "YOUR URI", token = "YOUR TOKEN")

Pivotting to wider format diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 0dd08dd..9d814e6 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -3,5 +3,5 @@ pkgdown: 2.0.7 pkgdown_sha: ~ articles: Introduction: Introduction.html -last_built: 2023-04-14T07:46Z +last_built: 2023-04-14T09:45Z diff --git a/docs/reference/clean_redcap_name.html b/docs/reference/clean_redcap_name.html new file mode 100644 index 0000000..1a71175 --- /dev/null +++ b/docs/reference/clean_redcap_name.html @@ -0,0 +1,101 @@ + +clean_redcap_name — clean_redcap_name • REDCapCAST + Skip to contents + + +
+
+
+

clean_redcap_name

+ Source: R/utils.r +
clean_redcap_name.Rd
+
+ +
+

Stepwise removal on non-alphanumeric characters, trailing white space, +substitutes spaces for underscores and converts to lower case. +Trying to make up for different naming conventions.

+
+ +
+

Usage

+ 
clean_redcap_name(x)
+
+ +
+

Arguments

+
x
+

vector or data frame for cleaning

+ +
+
+

Value

+ + +

vector or data frame, same format as input

+
+ +
+ + +
+

Developed by Andreas Gammelgaard Damsbo, Paul Egeler.

+
+ +
+

Site built with pkgdown 2.0.7.

+
+ +
+ + + + + + + diff --git a/docs/reference/index.html b/docs/reference/index.html index 4dabbc4..0ff3a01 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -67,6 +67,11 @@
Split REDCap repeating instruments table into multiple tables
+ clean_redcap_name() +
+
clean_redcap_name
+
+ focused_metadata()
focused_metadata
diff --git a/docs/reference/redcapcast_data.html b/docs/reference/redcapcast_data.html index 2b79da0..e41f792 100644 --- a/docs/reference/redcapcast_data.html +++ b/docs/reference/redcapcast_data.html @@ -107,7 +107,7 @@ Contains only synthetic data.

region

region, character

-
base_complete
+
baseline_data_start_complete

Completed, character

mrs_assessed
@@ -128,7 +128,7 @@ Contains only synthetic data.

event_type

Event type, character

-
event_complete
+
new_event_complete

Completed, character

diff --git a/docs/search.json b/docs/search.json index 0012f3d..39b9db1 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. General Public Licenses designed make sure freedom distribute copies free software (charge wish), receive source code can get want , can change software use pieces new free programs, know can things. protect rights, need prevent others denying rights asking surrender rights. Therefore, certain responsibilities distribute copies software, modify : responsibilities respect freedom others. example, distribute copies program, whether gratis fee, must pass recipients freedoms received. must make sure , , receive can get source code. must show terms know rights. 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END TERMS CONDITIONS","code":""},{"path":"/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":" Copyright (C) This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . Copyright (C) This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"/articles/Introduction.html","id":"splitting-the-dataset","dir":"Articles","previous_headings":"","what":"Splitting the dataset","title":"Introduction","text":"","code":"redcapcast_data |> gt::gt() redcapcast_meta |> gt::gt() list <- REDCapCAST::REDCap_split(records = redcapcast_data, metadata = redcapcast_meta, forms = \"repeating\") str(list) #> List of 2 #> $ :'data.frame': 9 obs. of 20 variables: #> ..$ record_id : num [1:9] 1 2 2 3 3 3 4 4 5 #> ..$ redcap_event_name: chr [1:9] \"inclusion\" \"inclusion\" \"follow1\" \"inclusion\" ... #> ..$ cpr : chr [1:9] \"1203401OB4\" \"0102342303\" NA \"2301569823\" ... #> ..$ inclusion : Date[1:9], format: \"2023-03-13\" \"2023-03-01\" ... #> ..$ dob : Date[1:9], format: \"1940-03-12\" \"1934-02-01\" ... #> ..$ age : num [1:9] 83 89.1 NA 66.1 NA ... #> ..$ age_integer : num [1:9] 83 89 NA 66 NA NA 117 NA 126 #> ..$ sex : chr [1:9] \"female\" \"male\" NA \"male\" ... #> ..$ cohabitation : chr [1:9] \"Yes\" \"Yes\" NA \"No\" ... #> ..$ hypertension : chr [1:9] \"No\" \"No\" NA \"Yes\" ... #> ..$ diabetes : chr [1:9] \"Yes\" \"No\" NA \"Yes\" ... #> ..$ region : chr [1:9] \"East\" \"South\" NA \"North\" ... #> ..$ base_complete : chr [1:9] \"Incomplete\" \"Incomplete\" NA \"Incomplete\" ... #> ..$ mrs_assessed : chr [1:9] \"Yes\" \"Yes\" \"Yes\" NA ... #> ..$ mrs_date : Date[1:9], format: \"2023-03-13\" \"2023-03-07\" ... #> ..$ mrs_score : num [1:9] 1 1 3 NA 2 1 NA NA NA #> ..$ mrs_complete : chr [1:9] \"Incomplete\" \"Incomplete\" \"Incomplete\" \"Incomplete\" ... #> ..$ event_date : Date[1:9], format: NA NA ... #> ..$ event_type : chr [1:9] NA NA NA NA ... #> ..$ event_complete : chr [1:9] NA NA NA NA ... #> $ Event:'data.frame': 9 obs. of 4 variables: #> ..$ record_id : num [1:9] 2 3 3 3 3 3 4 4 4 #> ..$ redcap_event_name : chr [1:9] \"follow1\" \"follow1\" \"follow1\" \"follow2\" ... #> ..$ redcap_repeat_instrument: chr [1:9] \"Event\" \"Event\" \"Event\" \"Event\" ... #> ..$ redcap_repeat_instance : num [1:9] 1 1 2 1 2 3 1 2 3 list <- REDCapCAST::REDCap_split(records = redcapcast_data, metadata = redcapcast_meta, forms = \"all\") str(list) #> List of 4 #> $ base :'data.frame': 9 obs. of 13 variables: #> ..$ record_id : num [1:9] 1 2 2 3 3 3 4 4 5 #> ..$ redcap_event_name: chr [1:9] \"inclusion\" \"inclusion\" \"follow1\" \"inclusion\" ... #> ..$ cpr : chr [1:9] \"1203401OB4\" \"0102342303\" NA \"2301569823\" ... #> ..$ inclusion : Date[1:9], format: \"2023-03-13\" \"2023-03-01\" ... #> ..$ dob : Date[1:9], format: \"1940-03-12\" \"1934-02-01\" ... #> ..$ age : num [1:9] 83 89.1 NA 66.1 NA ... #> ..$ age_integer : num [1:9] 83 89 NA 66 NA NA 117 NA 126 #> ..$ sex : chr [1:9] \"female\" \"male\" NA \"male\" ... #> ..$ cohabitation : chr [1:9] \"Yes\" \"Yes\" NA \"No\" ... #> ..$ hypertension : chr [1:9] \"No\" \"No\" NA \"Yes\" ... #> ..$ diabetes : chr [1:9] \"Yes\" \"No\" NA \"Yes\" ... #> ..$ region : chr [1:9] \"East\" \"South\" NA \"North\" ... #> ..$ base_complete : chr [1:9] \"Incomplete\" \"Incomplete\" NA \"Incomplete\" ... #> $ mrs :'data.frame': 9 obs. of 6 variables: #> ..$ record_id : num [1:9] 1 2 2 3 3 3 4 4 5 #> ..$ redcap_event_name: chr [1:9] \"inclusion\" \"inclusion\" \"follow1\" \"inclusion\" ... #> ..$ mrs_assessed : chr [1:9] \"Yes\" \"Yes\" \"Yes\" NA ... #> ..$ mrs_date : Date[1:9], format: \"2023-03-13\" \"2023-03-07\" ... #> ..$ mrs_score : num [1:9] 1 1 3 NA 2 1 NA NA NA #> ..$ mrs_complete : chr [1:9] \"Incomplete\" \"Incomplete\" \"Incomplete\" \"Incomplete\" ... #> $ event:'data.frame': 9 obs. of 5 variables: #> ..$ record_id : num [1:9] 1 2 2 3 3 3 4 4 5 #> ..$ redcap_event_name: chr [1:9] \"inclusion\" \"inclusion\" \"follow1\" \"inclusion\" ... #> ..$ event_date : Date[1:9], format: NA NA ... #> ..$ event_type : chr [1:9] NA NA NA NA ... #> ..$ event_complete : chr [1:9] NA NA NA NA ... #> $ Event:'data.frame': 9 obs. of 4 variables: #> ..$ record_id : num [1:9] 2 3 3 3 3 3 4 4 4 #> ..$ redcap_event_name : chr [1:9] \"follow1\" \"follow1\" \"follow1\" \"follow2\" ... #> ..$ redcap_repeat_instrument: chr [1:9] \"Event\" \"Event\" \"Event\" \"Event\" ... #> ..$ redcap_repeat_instance : num [1:9] 1 1 2 1 2 3 1 2 3"},{"path":"/articles/Introduction.html","id":"reading-data-from-redcap","dir":"Articles","previous_headings":"","what":"Reading data from REDCap","title":"Introduction","text":"function wraps demonstrated function get dataset, metadata, apply REDCap_splitfunction bit cleaning. function works similar REDCapR::redcap_read().","code":"# read_redcap_tables(uri = \"YOUR URI\", token = \"YOUR TOKEN\") # ds <- read_redcap_tables(uri = key_get(\"DB_URI\"), token = key_get(\"cast_api\"))"},{"path":"/articles/Introduction.html","id":"pivotting-to-wider-format","dir":"Articles","previous_headings":"","what":"Pivotting to wider format","title":"Introduction","text":"","code":"# redcap_wider(ds)"},{"path":"/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Andreas Gammelgaard Damsbo. Author, maintainer. Paul Egeler. Author.","code":""},{"path":"/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Damsbo , Egeler P (2023). REDCapCAST: REDCap Castellated Data Handling. R package version 23.4.1, https://github.com/agdamsbo/REDCapCAST.","code":"@Manual{, title = {REDCapCAST: REDCap Castellated Data Handling}, author = {Andreas Gammelgaard Damsbo and Paul Egeler}, year = {2023}, note = {R package version 23.4.1}, url = {https://github.com/agdamsbo/REDCapCAST}, }"},{"path":"/index.html","id":"redcapcast","dir":"","previous_headings":"","what":"REDCap Castellated Data Handling","title":"REDCap Castellated Data Handling","text":"REDCap Castellated data handling using repeated instruments. package fork SpectrumHealthResearch/REDCapRITS. REDCapRITS represents great extensive work handle castellated REDCap data different programming languages. fork purely minded R usage includes implementations main REDCap_split function. main goal project allow “minimal data” approach allowing filter records, instruments variables export download data needed. think approach desireable handling sensitive, clinical data. similar functionality available similar tools (like REDCapR REDCapTidieR). Please refer REDCap-Tools great tools.","code":""},{"path":"/index.html","id":"use-and-immprovements","dir":"","previous_headings":"","what":"Use and immprovements","title":"REDCap Castellated Data Handling","text":"package primarily relevant working longitudinal projects /projects using repeated instruments. just short descirption main functions: REDcap_split(): Works largely original REDCapRITS::REDCap_split(). takes REDCap dataset metadata (data dictionary) split data set list dataframes instruments. read_redcap_tables(): wraps use REDCapR::redcap_read() REDCap_split() ease export REDCap data. redcap_wider(): pivots data frame repeated instruments wide format utilizing tidyr::pivot_wider() tidyverse. Compared original REDCapRITS, matching functions improved accept column naming REDCap data manual download API export.","code":""},{"path":"/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"REDCap Castellated Data Handling","text":"Install latest version directly GitHub:","code":"remotes::install_github(\"agdamsbo/REDCapCAST\")"},{"path":"/reference/REDCap_split.html","id":null,"dir":"Reference","previous_headings":"","what":"Split REDCap repeating instruments table into multiple tables — REDCap_split","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"take output REDCap export split base table child tables repeating instrument. Metadata used determine fields included resultant table.","code":""},{"path":"/reference/REDCap_split.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"","code":"REDCap_split( records, metadata, primary_table_name = \"\", forms = c(\"repeating\", \"all\") )"},{"path":"/reference/REDCap_split.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"records Exported project records. May data.frame, response, character vector containing JSON API call. metadata Project metadata (data dictionary). May data.frame, response, character vector containing JSON API call. primary_table_name Name given list element primary output table (described README.md). Ignored forms = ''. forms Indicate whether create separate tables repeating instruments forms.","code":""},{"path":"/reference/REDCap_split.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"list \"data.frame\"s. number tables differ depending forms option selected. 'repeating': one base table one tables repeating instrument. '': data.frame instrument, regardless whether repeating instrument .","code":""},{"path":"/reference/REDCap_split.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"Paul W. Egeler, M.S., GStat","code":""},{"path":"/reference/REDCap_split.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"","code":"if (FALSE) { # Using an API call ------------------------------------------------------- library(RCurl) # Get the records records <- postForm( uri = api_url, # Supply your site-specific URI token = api_token, # Supply your own API token content = 'record', format = 'json', returnFormat = 'json' ) # Get the metadata metadata <- postForm( uri = api_url, # Supply your site-specific URI token = api_token, # Supply your own API token content = 'metadata', format = 'json' ) # Convert exported JSON strings into a list of data.frames REDCapRITS::REDCap_split(records, metadata) # Using a raw data export ------------------------------------------------- # Get the records records <- read.csv(\"/path/to/data/ExampleProject_DATA_2018-06-03_1700.csv\") # Get the metadata metadata <- read.csv( \"/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv\") # Split the tables REDCapRITS::REDCap_split(records, metadata) # In conjunction with the R export script --------------------------------- # You must set the working directory first since the REDCap data export # script contains relative file references. setwd(\"/path/to/data/\") # Run the data export script supplied by REDCap. # This will create a data.frame of your records called 'data' source(\"ExampleProject_R_2018-06-03_1700.r\") # Get the metadata metadata <- read.csv(\"ExampleProject_DataDictionary_2018-06-03.csv\") # Split the tables REDCapRITS::REDCap_split(data, metadata) }"},{"path":"/reference/focused_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"focused_metadata — focused_metadata","title":"focused_metadata — focused_metadata","text":"Extracts limited metadata variables dataset","code":""},{"path":"/reference/focused_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"focused_metadata — focused_metadata","text":"","code":"focused_metadata(metadata, vars_in_data)"},{"path":"/reference/focused_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"focused_metadata — focused_metadata","text":"metadata dataframe containing metadata vars_in_data Vector variable names dataset","code":""},{"path":"/reference/focused_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"focused_metadata — focused_metadata","text":"dataframe containing metadata variables dataset","code":""},{"path":"/reference/match_fields_to_form.html","id":null,"dir":"Reference","previous_headings":"","what":"Match fields to forms — match_fields_to_form","title":"Match fields to forms — match_fields_to_form","text":"Match fields forms","code":""},{"path":"/reference/match_fields_to_form.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Match fields to forms — match_fields_to_form","text":"","code":"match_fields_to_form(metadata, vars_in_data)"},{"path":"/reference/match_fields_to_form.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Match fields to forms — match_fields_to_form","text":"metadata data frame containing field names form names vars_in_data character vector variable names","code":""},{"path":"/reference/match_fields_to_form.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Match fields to forms — match_fields_to_form","text":"data frame containing field names form names","code":""},{"path":"/reference/read_redcap_tables.html","id":null,"dir":"Reference","previous_headings":"","what":"Download REDCap data — read_redcap_tables","title":"Download REDCap data — read_redcap_tables","text":"Implementation REDCap_split focused data acquisition approach using REDCapR::redcap_read nad downloading specified fields, forms /events using built-focused_metadata including clean-. Works longitudinal projects repeating instruments.","code":""},{"path":"/reference/read_redcap_tables.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download REDCap data — read_redcap_tables","text":"","code":"read_redcap_tables( uri, token, records = NULL, fields = NULL, events = NULL, forms = NULL, raw_or_label = \"label\", split_forms = \"all\", generics = c(\"record_id\", \"redcap_event_name\", \"redcap_repeat_instrument\", \"redcap_repeat_instance\") )"},{"path":"/reference/read_redcap_tables.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download REDCap data — read_redcap_tables","text":"uri REDCap database uri token API token records records download fields fields download events events download forms forms download raw_or_label raw label tags split_forms Whether split \"repeating\" \"\" forms, default . generics vector auto-generated generic variable names ignore discarding empty rows","code":""},{"path":"/reference/read_redcap_tables.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download REDCap data — read_redcap_tables","text":"list instruments","code":""},{"path":"/reference/read_redcap_tables.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download REDCap data — read_redcap_tables","text":"","code":"# Examples will be provided later"},{"path":"/reference/redcap_wider.html","id":null,"dir":"Reference","previous_headings":"","what":"Redcap Wider — redcap_wider","title":"Redcap Wider — redcap_wider","text":"Converts list REDCap data frames long wide format. Handles longitudinal projects, yet repeated instruments.","code":""},{"path":"/reference/redcap_wider.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Redcap Wider — redcap_wider","text":"","code":"redcap_wider( list, event.glue = \"{.value}_{redcap_event_name}\", inst.glue = \"{.value}_{redcap_repeat_instance}\" )"},{"path":"/reference/redcap_wider.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Redcap Wider — redcap_wider","text":"list list data frames. event.glue dplyr::glue string repeated events naming inst.glue dplyr::glue string repeated instruments naming","code":""},{"path":"/reference/redcap_wider.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Redcap Wider — redcap_wider","text":"list data frames wide format.","code":""},{"path":"/reference/redcap_wider.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Redcap Wider — redcap_wider","text":"","code":"list <- list(data.frame(record_id = c(1,2,1,2), redcap_event_name = c(\"baseline\", \"baseline\", \"followup\", \"followup\"), age = c(25,26,27,28)), data.frame(record_id = c(1,2), redcap_event_name = c(\"baseline\", \"baseline\"), gender = c(\"male\", \"female\"))) redcap_wider(list) #> Joining with `by = join_by(record_id)` #> record_id age_baseline age_followup gender #> 1 1 25 27 male #> 2 2 26 28 female"},{"path":"/reference/redcapcast_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Data set for demonstration — redcapcast_data","title":"Data set for demonstration — redcapcast_data","text":"small dataset REDCap database demonstrational purposes. Contains synthetic data.","code":""},{"path":"/reference/redcapcast_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data set for demonstration — redcapcast_data","text":"","code":"data(redcapcast_data)"},{"path":"/reference/redcapcast_data.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data set for demonstration — redcapcast_data","text":"data frame 22 variables: record_id ID, numeric redcap_event_name Event name, character redcap_repeat_instrument Repeat instrument, character redcap_repeat_instance Repeat instance, numeric cpr CPR number, character inclusion Inclusion date, date dob Date birth, date age Age decimal, numeric age_integer Age integer, numeric sex Legal sex, character cohabitation Cohabitation status, character hypertension Hypertension, character diabetes diabetes, character region region, character base_complete Completed, character mrs_assessed mRS Assessed, character mrs_date Assesment date, date mrs_score Score, numeric mrs_complete Complete, numeric event_date Event date, date event_type Event type, character event_complete Completed, character","code":""},{"path":"/reference/redcapcast_meta.html","id":null,"dir":"Reference","previous_headings":"","what":"REDCap metadata from data base — redcapcast_meta","title":"REDCap metadata from data base — redcapcast_meta","text":"metadata dataset REDCap database demonstrational purposes.","code":""},{"path":"/reference/redcapcast_meta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"REDCap metadata from data base — redcapcast_meta","text":"","code":"data(redcapcast_meta)"},{"path":"/reference/redcapcast_meta.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"REDCap metadata from data base — redcapcast_meta","text":"data frame 22 variables: field_name field_name, character form_name form_name, character section_header section_header, character field_type field_type, character field_label field_label, character select_choices_or_calculations select_choices_or_calculations, character field_note field_note, character text_validation_type_or_show_slider_number text_validation_type_or_show_slider_number, character text_validation_min text_validation_min, character text_validation_max text_validation_max, character identifier identifier, character branching_logic branching_logic, character required_field required_field, character custom_alignment custom_alignment, character question_number question_number, character matrix_group_name matrix_group_name, character matrix_ranking matrix_ranking, character field_annotation field_annotation, character","code":""},{"path":"/reference/sanitize_split.html","id":null,"dir":"Reference","previous_headings":"","what":"Sanitize list of data frames — sanitize_split","title":"Sanitize list of data frames — sanitize_split","text":"Removing empty rows","code":""},{"path":"/reference/sanitize_split.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sanitize list of data frames — sanitize_split","text":"","code":"sanitize_split( l, generic.names = c(\"record_id\", \"redcap_event_name\", \"redcap_repeat_instrument\", \"redcap_repeat_instance\") )"},{"path":"/reference/sanitize_split.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sanitize list of data frames — sanitize_split","text":"l list data frames. generic.names vector generic names excluded.","code":""},{"path":"/reference/sanitize_split.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sanitize list of data frames — sanitize_split","text":"list data frames generic names excluded.","code":""},{"path":"/reference/split_non_repeating_forms.html","id":null,"dir":"Reference","previous_headings":"","what":"Split a data frame into separate tables for each form — split_non_repeating_forms","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"Split data frame separate tables form","code":""},{"path":"/reference/split_non_repeating_forms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"","code":"split_non_repeating_forms(table, universal_fields, fields)"},{"path":"/reference/split_non_repeating_forms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"table data frame universal_fields character vector fields included every table fields two-column matrix containing names fields included form","code":""},{"path":"/reference/split_non_repeating_forms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"list data frames, one non-repeating form","code":""},{"path":"/reference/split_non_repeating_forms.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"","code":"# Create a table table <- data.frame( id = c(1, 2, 3, 4, 5), form_a_name = c(\"John\", \"Alice\", \"Bob\", \"Eve\", \"Mallory\"), form_a_age = c(25, 30, 25, 15, 20), form_b_name = c(\"John\", \"Alice\", \"Bob\", \"Eve\", \"Mallory\"), form_b_gender = c(\"M\", \"F\", \"M\", \"F\", \"F\") ) # Create the universal fields universal_fields <- c(\"id\") # Create the fields fields <- matrix( c(\"form_a_name\", \"form_a\", \"form_a_age\", \"form_a\", \"form_b_name\", \"form_b\", \"form_b_gender\", \"form_b\"), ncol = 2, byrow = TRUE ) # Split the table split_non_repeating_forms(table, universal_fields, fields) #> $form_a_age #> id #> 1 1 #> 2 2 #> 3 3 #> 4 4 #> 5 5 #>"},{"path":[]},{"path":"/news/index.html","id":"documentation-23-4-1","dir":"Changelog","previous_headings":"","what":"Documentation:","title":"REDCapCAST 23.4.1","text":"Aiming CRAN","code":""},{"path":[]},{"path":"/news/index.html","id":"documentation-23-3-2","dir":"Changelog","previous_headings":"","what":"Documentation:","title":"REDCapCAST 23.3.2","text":"Page added. Vignettes follow. GithubActions tests added code coverage assessed. Badge galore..","code":""},{"path":[]},{"path":"/news/index.html","id":"new-name-redcapcast-23-3-1","dir":"Changelog","previous_headings":"","what":"New name: REDCapCAST","title":"REDCapCAST 23.3.1","text":"reflect new functions limitation working R, changed naming fork, still, course, maintaining status fork. versioning moved monthly naming convention. main goal package keep option export defined subset whole dataset REDCap server made possible REDCapR::redcap_read() function, combine work put REDCapRITS package handling longitudinal projects /projects repeated instruments.","code":""},{"path":"/news/index.html","id":"functions-23-3-1","dir":"Changelog","previous_headings":"","what":"Functions:","title":"REDCapCAST 23.3.1","text":"read_redcap_tables() NEW: function mainly implementation combined use REDCapR::readcap_read() REDCap_split() maintain focused nature REDCapR::readcap_read(), download specified data. Also implements tests valid form names event names. usual fall-back solution get data. redcap_wider() NEW: function pivots long data frames read_redcap_tables() using tidyr::pivot_wider(). focused_metadata() NEW: hidden helper function enable focused data acquisition approach handle subset metadata corresponding focused dataset.","code":""},{"path":"/news/index.html","id":"notes-23-3-1","dir":"Changelog","previous_headings":"","what":"Notes:","title":"REDCapCAST 23.3.1","text":"metadata handling IMPROVED: improved handling different column names matadata (DataDictionary) REDCap dependent whether acquired thorugh api og downloaded server.","code":""}] +[{"path":"/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"/articles/Introduction.html","id":"splitting-the-dataset","dir":"Articles","previous_headings":"","what":"Splitting the dataset","title":"Introduction","text":"","code":"redcapcast_data |> gt::gt() redcapcast_meta |> gt::gt() list <- REDCap_split(records = redcapcast_data, metadata = redcapcast_meta, forms = \"repeating\") str(list) #> List of 2 #> $ :'data.frame': 9 obs. of 17 variables: #> ..$ record_id : num [1:9] 1 2 2 3 3 3 4 4 5 #> ..$ redcap_event_name : chr [1:9] \"inclusion\" \"inclusion\" \"follow1\" \"inclusion\" ... #> ..$ cpr : chr [1:9] \"1203401OB4\" \"0102342303\" NA \"2301569823\" ... #> ..$ inclusion : Date[1:9], format: \"2023-03-13\" \"2023-03-01\" ... #> ..$ dob : Date[1:9], format: \"1940-03-12\" \"1934-02-01\" ... #> ..$ age : num [1:9] 83 89.1 NA 66.1 NA ... #> ..$ age_integer : num [1:9] 83 89 NA 66 NA NA 117 NA 126 #> ..$ sex : chr [1:9] \"female\" \"male\" NA \"male\" ... #> ..$ cohabitation : chr [1:9] \"Yes\" \"Yes\" NA \"No\" ... #> ..$ hypertension : chr [1:9] \"No\" \"No\" NA \"Yes\" ... #> ..$ diabetes : chr [1:9] \"Yes\" \"No\" NA \"Yes\" ... #> ..$ region : chr [1:9] \"East\" \"South\" NA \"North\" ... #> ..$ baseline_data_start_complete: chr [1:9] \"Incomplete\" \"Incomplete\" NA \"Incomplete\" ... #> ..$ mrs_assessed : chr [1:9] \"Yes\" \"Yes\" \"Yes\" NA ... #> ..$ mrs_date : Date[1:9], format: \"2023-03-13\" \"2023-03-07\" ... #> ..$ mrs_score : num [1:9] 1 1 3 NA 2 1 NA NA NA #> ..$ mrs_complete : chr [1:9] \"Incomplete\" \"Incomplete\" \"Incomplete\" \"Incomplete\" ... #> $ new_event:'data.frame': 9 obs. of 7 variables: #> ..$ record_id : num [1:9] 2 3 3 3 3 3 4 4 4 #> ..$ redcap_event_name : chr [1:9] \"follow1\" \"follow1\" \"follow1\" \"follow2\" ... #> ..$ redcap_repeat_instrument: chr [1:9] \"new_event\" \"new_event\" \"new_event\" \"new_event\" ... #> ..$ redcap_repeat_instance : num [1:9] 1 1 2 1 2 3 1 2 3 #> ..$ event_date : Date[1:9], format: \"2023-03-13\" \"2022-11-08\" ... #> ..$ event_type : chr [1:9] \"TIA\" \"AIS\" \"ICH\" \"ICH\" ... #> ..$ new_event_complete : chr [1:9] \"Incomplete\" \"Incomplete\" \"Incomplete\" \"Incomplete\" ... list <- REDCap_split(records = redcapcast_data, metadata = redcapcast_meta, forms = \"all\") str(list) #> List of 3 #> $ baseline_data_start:'data.frame': 9 obs. of 13 variables: #> ..$ record_id : num [1:9] 1 2 2 3 3 3 4 4 5 #> ..$ redcap_event_name : chr [1:9] \"inclusion\" \"inclusion\" \"follow1\" \"inclusion\" ... #> ..$ cpr : chr [1:9] \"1203401OB4\" \"0102342303\" NA \"2301569823\" ... #> ..$ inclusion : Date[1:9], format: \"2023-03-13\" \"2023-03-01\" ... #> ..$ dob : Date[1:9], format: \"1940-03-12\" \"1934-02-01\" ... #> ..$ age : num [1:9] 83 89.1 NA 66.1 NA ... #> ..$ age_integer : num [1:9] 83 89 NA 66 NA NA 117 NA 126 #> ..$ sex : chr [1:9] \"female\" \"male\" NA \"male\" ... #> ..$ cohabitation : chr [1:9] \"Yes\" \"Yes\" NA \"No\" ... #> ..$ hypertension : chr [1:9] \"No\" \"No\" NA \"Yes\" ... #> ..$ diabetes : chr [1:9] \"Yes\" \"No\" NA \"Yes\" ... #> ..$ region : chr [1:9] \"East\" \"South\" NA \"North\" ... #> ..$ baseline_data_start_complete: chr [1:9] \"Incomplete\" \"Incomplete\" NA \"Incomplete\" ... #> $ mrs :'data.frame': 9 obs. of 6 variables: #> ..$ record_id : num [1:9] 1 2 2 3 3 3 4 4 5 #> ..$ redcap_event_name: chr [1:9] \"inclusion\" \"inclusion\" \"follow1\" \"inclusion\" ... #> ..$ mrs_assessed : chr [1:9] \"Yes\" \"Yes\" \"Yes\" NA ... #> ..$ mrs_date : Date[1:9], format: \"2023-03-13\" \"2023-03-07\" ... #> ..$ mrs_score : num [1:9] 1 1 3 NA 2 1 NA NA NA #> ..$ mrs_complete : chr [1:9] \"Incomplete\" \"Incomplete\" \"Incomplete\" \"Incomplete\" ... #> $ new_event :'data.frame': 9 obs. of 7 variables: #> ..$ record_id : num [1:9] 2 3 3 3 3 3 4 4 4 #> ..$ redcap_event_name : chr [1:9] \"follow1\" \"follow1\" \"follow1\" \"follow2\" ... #> ..$ redcap_repeat_instrument: chr [1:9] \"new_event\" \"new_event\" \"new_event\" \"new_event\" ... #> ..$ redcap_repeat_instance : num [1:9] 1 1 2 1 2 3 1 2 3 #> ..$ event_date : Date[1:9], format: \"2023-03-13\" \"2022-11-08\" ... #> ..$ event_type : chr [1:9] \"TIA\" \"AIS\" \"ICH\" \"ICH\" ... #> ..$ new_event_complete : chr [1:9] \"Incomplete\" \"Incomplete\" \"Incomplete\" \"Incomplete\" ..."},{"path":"/articles/Introduction.html","id":"reading-data-from-redcap","dir":"Articles","previous_headings":"","what":"Reading data from REDCap","title":"Introduction","text":"function wraps demonstrated function get dataset, metadata, apply REDCap_splitfunction bit cleaning. just cuts outs steps easier approach. function works similar REDCapR::redcap_read() allowing specify fields, events forms export instead exporting whole database filtering afterwards. believe better safer, focused approach.","code":"# read_redcap_tables(uri = \"YOUR URI\", token = \"YOUR TOKEN\")"},{"path":"/articles/Introduction.html","id":"pivotting-to-wider-format","dir":"Articles","previous_headings":"","what":"Pivotting to wider format","title":"Introduction","text":"","code":"# redcap_wider(ds)"},{"path":"/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Andreas Gammelgaard Damsbo. Author, maintainer. Paul Egeler. Author.","code":""},{"path":"/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Damsbo , Egeler P (2023). REDCapCAST: REDCap Castellated Data Handling. R package version 23.4.1, https://github.com/agdamsbo/REDCapCAST.","code":"@Manual{, title = {REDCapCAST: REDCap Castellated Data Handling}, author = {Andreas Gammelgaard Damsbo and Paul Egeler}, year = {2023}, note = {R package version 23.4.1}, url = {https://github.com/agdamsbo/REDCapCAST}, }"},{"path":"/index.html","id":"redcapcast","dir":"","previous_headings":"","what":"REDCap Castellated Data Handling","title":"REDCap Castellated Data Handling","text":"REDCap Castellated data handling using repeated instruments. package fork SpectrumHealthResearch/REDCapRITS. REDCapRITS represents great extensive work handle castellated REDCap data different programming languages. fork purely minded R usage includes implementations main REDCap_split function. main goal project allow “minimal data” approach allowing filter records, instruments variables export download data needed. think approach desireable handling sensitive, clinical data. similar functionality available similar tools (like REDCapR REDCapTidieR). Please refer REDCap-Tools great tools.","code":""},{"path":"/index.html","id":"use-and-immprovements","dir":"","previous_headings":"","what":"Use and immprovements","title":"REDCap Castellated Data Handling","text":"package primarily relevant working longitudinal projects /projects using repeated instruments. just short descirption main functions: REDcap_split(): Works largely original REDCapRITS::REDCap_split(). takes REDCap dataset metadata (data dictionary) split data set list dataframes instruments. read_redcap_tables(): wraps use REDCapR::redcap_read() REDCap_split() ease export REDCap data. redcap_wider(): pivots data frame repeated instruments wide format utilizing tidyr::pivot_wider() tidyverse. Compared original REDCapRITS, matching functions improved accept column naming REDCap data manual download API export.","code":""},{"path":"/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"REDCap Castellated Data Handling","text":"Install latest version directly GitHub:","code":"remotes::install_github(\"agdamsbo/REDCapCAST\")"},{"path":"/reference/REDCap_split.html","id":null,"dir":"Reference","previous_headings":"","what":"Split REDCap repeating instruments table into multiple tables — REDCap_split","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"take output REDCap export split base table child tables repeating instrument. Metadata used determine fields included resultant table.","code":""},{"path":"/reference/REDCap_split.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"","code":"REDCap_split( records, metadata, primary_table_name = \"\", forms = c(\"repeating\", \"all\") )"},{"path":"/reference/REDCap_split.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"records Exported project records. May data.frame, response, character vector containing JSON API call. metadata Project metadata (data dictionary). May data.frame, response, character vector containing JSON API call. primary_table_name Name given list element primary output table (described README.md). Ignored forms = ''. forms Indicate whether create separate tables repeating instruments forms.","code":""},{"path":"/reference/REDCap_split.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"list \"data.frame\"s. number tables differ depending forms option selected. 'repeating': one base table one tables repeating instrument. '': data.frame instrument, regardless whether repeating instrument .","code":""},{"path":"/reference/REDCap_split.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"Paul W. Egeler, M.S., GStat","code":""},{"path":"/reference/REDCap_split.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"","code":"if (FALSE) { # Using an API call ------------------------------------------------------- library(RCurl) # Get the records records <- postForm( uri = api_url, # Supply your site-specific URI token = api_token, # Supply your own API token content = 'record', format = 'json', returnFormat = 'json' ) # Get the metadata metadata <- postForm( uri = api_url, # Supply your site-specific URI token = api_token, # Supply your own API token content = 'metadata', format = 'json' ) # Convert exported JSON strings into a list of data.frames REDCapRITS::REDCap_split(records, metadata) # Using a raw data export ------------------------------------------------- # Get the records records <- read.csv(\"/path/to/data/ExampleProject_DATA_2018-06-03_1700.csv\") # Get the metadata metadata <- read.csv( \"/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv\") # Split the tables REDCapRITS::REDCap_split(records, metadata) # In conjunction with the R export script --------------------------------- # You must set the working directory first since the REDCap data export # script contains relative file references. setwd(\"/path/to/data/\") # Run the data export script supplied by REDCap. # This will create a data.frame of your records called 'data' source(\"ExampleProject_R_2018-06-03_1700.r\") # Get the metadata metadata <- read.csv(\"ExampleProject_DataDictionary_2018-06-03.csv\") # Split the tables REDCapRITS::REDCap_split(data, metadata) }"},{"path":"/reference/clean_redcap_name.html","id":null,"dir":"Reference","previous_headings":"","what":"clean_redcap_name — clean_redcap_name","title":"clean_redcap_name — clean_redcap_name","text":"Stepwise removal non-alphanumeric characters, trailing white space, substitutes spaces underscores converts lower case. Trying make different naming conventions.","code":""},{"path":"/reference/clean_redcap_name.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"clean_redcap_name — clean_redcap_name","text":"","code":"clean_redcap_name(x)"},{"path":"/reference/clean_redcap_name.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"clean_redcap_name — clean_redcap_name","text":"x vector data frame cleaning","code":""},{"path":"/reference/clean_redcap_name.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"clean_redcap_name — clean_redcap_name","text":"vector data frame, format input","code":""},{"path":"/reference/focused_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"focused_metadata — focused_metadata","title":"focused_metadata — focused_metadata","text":"Extracts limited metadata variables dataset","code":""},{"path":"/reference/focused_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"focused_metadata — focused_metadata","text":"","code":"focused_metadata(metadata, vars_in_data)"},{"path":"/reference/focused_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"focused_metadata — focused_metadata","text":"metadata dataframe containing metadata vars_in_data Vector variable names dataset","code":""},{"path":"/reference/focused_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"focused_metadata — focused_metadata","text":"dataframe containing metadata variables dataset","code":""},{"path":"/reference/match_fields_to_form.html","id":null,"dir":"Reference","previous_headings":"","what":"Match fields to forms — match_fields_to_form","title":"Match fields to forms — match_fields_to_form","text":"Match fields forms","code":""},{"path":"/reference/match_fields_to_form.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Match fields to forms — match_fields_to_form","text":"","code":"match_fields_to_form(metadata, vars_in_data)"},{"path":"/reference/match_fields_to_form.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Match fields to forms — match_fields_to_form","text":"metadata data frame containing field names form names vars_in_data character vector variable names","code":""},{"path":"/reference/match_fields_to_form.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Match fields to forms — match_fields_to_form","text":"data frame containing field names form names","code":""},{"path":"/reference/read_redcap_tables.html","id":null,"dir":"Reference","previous_headings":"","what":"Download REDCap data — read_redcap_tables","title":"Download REDCap data — read_redcap_tables","text":"Implementation REDCap_split focused data acquisition approach using REDCapR::redcap_read nad downloading specified fields, forms /events using built-focused_metadata including clean-. Works longitudinal projects repeating instruments.","code":""},{"path":"/reference/read_redcap_tables.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download REDCap data — read_redcap_tables","text":"","code":"read_redcap_tables( uri, token, records = NULL, fields = NULL, events = NULL, forms = NULL, raw_or_label = \"label\", split_forms = \"all\", generics = c(\"record_id\", \"redcap_event_name\", \"redcap_repeat_instrument\", \"redcap_repeat_instance\") )"},{"path":"/reference/read_redcap_tables.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download REDCap data — read_redcap_tables","text":"uri REDCap database uri token API token records records download fields fields download events events download forms forms download raw_or_label raw label tags split_forms Whether split \"repeating\" \"\" forms, default . generics vector auto-generated generic variable names ignore discarding empty rows","code":""},{"path":"/reference/read_redcap_tables.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download REDCap data — read_redcap_tables","text":"list instruments","code":""},{"path":"/reference/read_redcap_tables.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download REDCap data — read_redcap_tables","text":"","code":"# Examples will be provided later"},{"path":"/reference/redcap_wider.html","id":null,"dir":"Reference","previous_headings":"","what":"Redcap Wider — redcap_wider","title":"Redcap Wider — redcap_wider","text":"Converts list REDCap data frames long wide format. Handles longitudinal projects, yet repeated instruments.","code":""},{"path":"/reference/redcap_wider.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Redcap Wider — redcap_wider","text":"","code":"redcap_wider( list, event.glue = \"{.value}_{redcap_event_name}\", inst.glue = \"{.value}_{redcap_repeat_instance}\" )"},{"path":"/reference/redcap_wider.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Redcap Wider — redcap_wider","text":"list list data frames. event.glue dplyr::glue string repeated events naming inst.glue dplyr::glue string repeated instruments naming","code":""},{"path":"/reference/redcap_wider.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Redcap Wider — redcap_wider","text":"list data frames wide format.","code":""},{"path":"/reference/redcap_wider.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Redcap Wider — redcap_wider","text":"","code":"list <- list(data.frame(record_id = c(1,2,1,2), redcap_event_name = c(\"baseline\", \"baseline\", \"followup\", \"followup\"), age = c(25,26,27,28)), data.frame(record_id = c(1,2), redcap_event_name = c(\"baseline\", \"baseline\"), gender = c(\"male\", \"female\"))) redcap_wider(list) #> Joining with `by = join_by(record_id)` #> record_id age_baseline age_followup gender #> 1 1 25 27 male #> 2 2 26 28 female"},{"path":"/reference/redcapcast_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Data set for demonstration — redcapcast_data","title":"Data set for demonstration — redcapcast_data","text":"small dataset REDCap database demonstrational purposes. Contains synthetic data.","code":""},{"path":"/reference/redcapcast_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Data set for demonstration — redcapcast_data","text":"","code":"data(redcapcast_data)"},{"path":"/reference/redcapcast_data.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data set for demonstration — redcapcast_data","text":"data frame 22 variables: record_id ID, numeric redcap_event_name Event name, character redcap_repeat_instrument Repeat instrument, character redcap_repeat_instance Repeat instance, numeric cpr CPR number, character inclusion Inclusion date, date dob Date birth, date age Age decimal, numeric age_integer Age integer, numeric sex Legal sex, character cohabitation Cohabitation status, character hypertension Hypertension, character diabetes diabetes, character region region, character baseline_data_start_complete Completed, character mrs_assessed mRS Assessed, character mrs_date Assesment date, date mrs_score Score, numeric mrs_complete Complete, numeric event_date Event date, date event_type Event type, character new_event_complete Completed, character","code":""},{"path":"/reference/redcapcast_meta.html","id":null,"dir":"Reference","previous_headings":"","what":"REDCap metadata from data base — redcapcast_meta","title":"REDCap metadata from data base — redcapcast_meta","text":"metadata dataset REDCap database demonstrational purposes.","code":""},{"path":"/reference/redcapcast_meta.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"REDCap metadata from data base — redcapcast_meta","text":"","code":"data(redcapcast_meta)"},{"path":"/reference/redcapcast_meta.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"REDCap metadata from data base — redcapcast_meta","text":"data frame 22 variables: field_name field_name, character form_name form_name, character section_header section_header, character field_type field_type, character field_label field_label, character select_choices_or_calculations select_choices_or_calculations, character field_note field_note, character text_validation_type_or_show_slider_number text_validation_type_or_show_slider_number, character text_validation_min text_validation_min, character text_validation_max text_validation_max, character identifier identifier, character branching_logic branching_logic, character required_field required_field, character custom_alignment custom_alignment, character question_number question_number, character matrix_group_name matrix_group_name, character matrix_ranking matrix_ranking, character field_annotation field_annotation, character","code":""},{"path":"/reference/sanitize_split.html","id":null,"dir":"Reference","previous_headings":"","what":"Sanitize list of data frames — sanitize_split","title":"Sanitize list of data frames — sanitize_split","text":"Removing empty rows","code":""},{"path":"/reference/sanitize_split.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Sanitize list of data frames — sanitize_split","text":"","code":"sanitize_split( l, generic.names = c(\"record_id\", \"redcap_event_name\", \"redcap_repeat_instrument\", \"redcap_repeat_instance\") )"},{"path":"/reference/sanitize_split.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Sanitize list of data frames — sanitize_split","text":"l list data frames. generic.names vector generic names excluded.","code":""},{"path":"/reference/sanitize_split.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Sanitize list of data frames — sanitize_split","text":"list data frames generic names excluded.","code":""},{"path":"/reference/split_non_repeating_forms.html","id":null,"dir":"Reference","previous_headings":"","what":"Split a data frame into separate tables for each form — split_non_repeating_forms","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"Split data frame separate tables form","code":""},{"path":"/reference/split_non_repeating_forms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"","code":"split_non_repeating_forms(table, universal_fields, fields)"},{"path":"/reference/split_non_repeating_forms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"table data frame universal_fields character vector fields included every table fields two-column matrix containing names fields included form","code":""},{"path":"/reference/split_non_repeating_forms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"list data frames, one non-repeating form","code":""},{"path":"/reference/split_non_repeating_forms.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split a data frame into separate tables for each form — split_non_repeating_forms","text":"","code":"# Create a table table <- data.frame( id = c(1, 2, 3, 4, 5), form_a_name = c(\"John\", \"Alice\", \"Bob\", \"Eve\", \"Mallory\"), form_a_age = c(25, 30, 25, 15, 20), form_b_name = c(\"John\", \"Alice\", \"Bob\", \"Eve\", \"Mallory\"), form_b_gender = c(\"M\", \"F\", \"M\", \"F\", \"F\") ) # Create the universal fields universal_fields <- c(\"id\") # Create the fields fields <- matrix( c(\"form_a_name\", \"form_a\", \"form_a_age\", \"form_a\", \"form_b_name\", \"form_b\", \"form_b_gender\", \"form_b\"), ncol = 2, byrow = TRUE ) # Split the table split_non_repeating_forms(table, universal_fields, fields) #> $form_a_age #> id #> 1 1 #> 2 2 #> 3 3 #> 4 4 #> 5 5 #>"},{"path":[]},{"path":"/news/index.html","id":"documentation-23-4-1","dir":"Changelog","previous_headings":"","what":"Documentation:","title":"REDCapCAST 23.4.1","text":"Aiming CRAN","code":""},{"path":[]},{"path":"/news/index.html","id":"documentation-23-3-2","dir":"Changelog","previous_headings":"","what":"Documentation:","title":"REDCapCAST 23.3.2","text":"Page added. Vignettes follow. GithubActions tests added code coverage assessed. Badge galore..","code":""},{"path":[]},{"path":"/news/index.html","id":"new-name-redcapcast-23-3-1","dir":"Changelog","previous_headings":"","what":"New name: REDCapCAST","title":"REDCapCAST 23.3.1","text":"reflect new functions limitation working R, changed naming fork, still, course, maintaining status fork. versioning moved monthly naming convention. main goal package keep option export defined subset whole dataset REDCap server made possible REDCapR::redcap_read() function, combine work put REDCapRITS package handling longitudinal projects /projects repeated instruments.","code":""},{"path":"/news/index.html","id":"functions-23-3-1","dir":"Changelog","previous_headings":"","what":"Functions:","title":"REDCapCAST 23.3.1","text":"read_redcap_tables() NEW: function mainly implementation combined use REDCapR::readcap_read() REDCap_split() maintain focused nature REDCapR::readcap_read(), download specified data. Also implements tests valid form names event names. usual fall-back solution get data. redcap_wider() NEW: function pivots long data frames read_redcap_tables() using tidyr::pivot_wider(). focused_metadata() NEW: hidden helper function enable focused data acquisition approach handle subset metadata corresponding focused dataset.","code":""},{"path":"/news/index.html","id":"notes-23-3-1","dir":"Changelog","previous_headings":"","what":"Notes:","title":"REDCapCAST 23.3.1","text":"metadata handling IMPROVED: improved handling different column names matadata (DataDictionary) REDCap dependent whether acquired thorugh api og downloaded server.","code":""}] diff --git a/docs/sitemap.xml b/docs/sitemap.xml index db26244..50fe1f1 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -24,6 +24,9 @@ /reference/REDCap_split.html + + /reference/clean_redcap_name.html + /reference/focused_metadata.html diff --git a/man/clean_redcap_name.Rd b/man/clean_redcap_name.Rd new file mode 100644 index 0000000..18b16a8 --- /dev/null +++ b/man/clean_redcap_name.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/utils.r +\name{clean_redcap_name} +\alias{clean_redcap_name} +\title{clean_redcap_name} +\usage{ +clean_redcap_name(x) +} +\arguments{ +\item{x}{vector or data frame for cleaning} +} +\value{ +vector or data frame, same format as input +} +\description{ +Stepwise removal on non-alphanumeric characters, trailing white space, +substitutes spaces for underscores and converts to lower case. +Trying to make up for different naming conventions. +} diff --git a/man/redcapcast_data.Rd b/man/redcapcast_data.Rd index 0e29927..0f7696f 100644 --- a/man/redcapcast_data.Rd +++ b/man/redcapcast_data.Rd @@ -21,14 +21,14 @@ A data frame with 22 variables: \item{hypertension}{Hypertension, character} \item{diabetes}{diabetes, character} \item{region}{region, character} - \item{base_complete}{Completed, character} + \item{baseline_data_start_complete}{Completed, character} \item{mrs_assessed}{mRS Assessed, character} \item{mrs_date}{Assesment date, date} \item{mrs_score}{Score, numeric} \item{mrs_complete}{Complete, numeric} \item{event_date}{Event date, date} \item{event_type}{Event type, character} - \item{event_complete}{Completed, character} + \item{new_event_complete}{Completed, character} } } diff --git a/tests/testthat/helper-paths.R b/tests/testthat/helper-paths.R index 68f9e0c..5a1607d 100644 --- a/tests/testthat/helper-paths.R +++ b/tests/testthat/helper-paths.R @@ -6,5 +6,7 @@ # ) # } +# setwd("tests/testthat") + get_data_location <- function(x) file.path("data", x) diff --git a/tests/testthat/test-csv-exports.R b/tests/testthat/test-csv-exports.R index cbcdabe..5ca6bb0 100644 --- a/tests/testthat/test-csv-exports.R +++ b/tests/testthat/test-csv-exports.R @@ -14,7 +14,7 @@ redcap_output_csv1 <- REDCap_split(records, metadata) # Test that basic CSV export matches reference ------------------------------ test_that("CSV export matches reference", { - expect_known_hash(redcap_output_csv1, "f74558d1939c17d9ff0e08a19b956e26") + expect_known_hash(redcap_output_csv1, "cb5074a06e1abcf659d60be1016965d2") }) # Test that REDCap_split can handle a focused dataset @@ -41,7 +41,7 @@ if (requireNamespace("Hmisc", quietly = TRUE)) { redcap_output_csv2 <- REDCap_split(REDCap_process_csv(records), metadata) - expect_known_hash(redcap_output_csv2, "6d8d0462ab2343b848a086ab06b50fe3") + expect_known_hash(redcap_output_csv2, "578dc054e59ec92a21e950042e08ee37") }) } diff --git a/vignettes/Introduction.Rmd b/vignettes/Introduction.Rmd index 314cfb2..bf390dd 100644 --- a/vignettes/Introduction.Rmd +++ b/vignettes/Introduction.Rmd @@ -33,7 +33,7 @@ redcapcast_meta |> gt::gt() ``` ```{r} list <- - REDCapCAST::REDCap_split(records = redcapcast_data, + REDCap_split(records = redcapcast_data, metadata = redcapcast_meta, forms = "repeating") str(list) @@ -41,7 +41,7 @@ str(list) ```{r} list <- - REDCapCAST::REDCap_split(records = redcapcast_data, + REDCap_split(records = redcapcast_data, metadata = redcapcast_meta, forms = "all") str(list) @@ -49,14 +49,12 @@ str(list) ## Reading data from REDCap -This function wraps all the above demonstrated function to get the dataset, the metadata, apply the `REDCap_split`function and then a bit of cleaning. +This function wraps all the above demonstrated function to get the dataset, the metadata, apply the `REDCap_split`function and then a bit of cleaning. It just cuts outs all the steps for an easier approach. -The function works very similar to the `REDCapR::redcap_read()`. +The function works very similar to the `REDCapR::redcap_read()` in allowing to specify fields, events and forms for export instead of exporting the whole database and filtering afterwards. I believe this is a better and safer, focused approach. ```{r eval=FALSE} # read_redcap_tables(uri = "YOUR URI", token = "YOUR TOKEN") - -# ds <- read_redcap_tables(uri = key_get("DB_URI"), token = key_get("cast_api")) ``` ## Pivotting to wider format