diff --git a/docs/articles/Introduction.html b/docs/articles/Introduction.html
index 43b7864..a8511c1 100644
--- a/docs/articles/Introduction.html
+++ b/docs/articles/Introduction.html
@@ -98,23 +98,23 @@ demonstration of the functions.</p>
 </h2>
 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">redcapcast_data</span> <span class="op">|&gt;</span> <span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/gt.html" class="external-link">gt</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
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@@ -1001,23 +1001,23 @@ demonstration of the functions.</p>
 </div>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">redcapcast_meta</span> <span class="op">|&gt;</span> <span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/gt.html" class="external-link">gt</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
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diff --git a/docs/index.html b/docs/index.html
index 786c708..87ffc33 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -8,16 +8,17 @@
 <meta name="description" content="Forked from REDCapRITS by Paul Egeler and Spectrum Health. 
     See &lt;https://github.com/SpectrumHealthResearch/REDCapRITS&gt;.
     Handles castellated datasets from REDCap projects with repeating instruments. 
-    Assists in splitting raw REDCap data exports to base table and child tables 
-    for each repeated instrument. Keeps a focused data export approach, by
-    allowing to only export required data from the database.
+    Assists in casting tidy tables from raw REDCap data exports for each 
+    repeated instrument. Keeps a focused data export approach, by allowing to 
+    only export required data from the database.
     REDCap (Research Electronic Data Capture) is a secure, web-based software
     platform designed to support data capture for research studies, providing
     1) an intuitive interface for validated data capture; 2) audit trails for
     tracking data manipulation and export procedures; 3) automated export
     procedures for seamless data downloads to common statistical packages; and
     4) procedures for data integration and interoperability with external sources
-    (&lt;doi:10.1016/j.jbi.2008.08.010&gt;; &lt;doi:10.1016/j.jbi.2019.103208&gt;).">
+    (Harris et al (2009) &lt;doi:10.1016/j.jbi.2008.08.010&gt;; 
+    Harris et al (2019) &lt;doi:10.1016/j.jbi.2019.103208&gt;).">
 <title>REDCap Castellated Data Handling • REDCapCAST</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png">
 <link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png">
@@ -33,16 +34,17 @@
 <meta property="og:description" content="Forked from REDCapRITS by Paul Egeler and Spectrum Health. 
     See &lt;https://github.com/SpectrumHealthResearch/REDCapRITS&gt;.
     Handles castellated datasets from REDCap projects with repeating instruments. 
-    Assists in splitting raw REDCap data exports to base table and child tables 
-    for each repeated instrument. Keeps a focused data export approach, by
-    allowing to only export required data from the database.
+    Assists in casting tidy tables from raw REDCap data exports for each 
+    repeated instrument. Keeps a focused data export approach, by allowing to 
+    only export required data from the database.
     REDCap (Research Electronic Data Capture) is a secure, web-based software
     platform designed to support data capture for research studies, providing
     1) an intuitive interface for validated data capture; 2) audit trails for
     tracking data manipulation and export procedures; 3) automated export
     procedures for seamless data downloads to common statistical packages; and
     4) procedures for data integration and interoperability with external sources
-    (&lt;doi:10.1016/j.jbi.2008.08.010&gt;; &lt;doi:10.1016/j.jbi.2019.103208&gt;).">
+    (Harris et al (2009) &lt;doi:10.1016/j.jbi.2008.08.010&gt;; 
+    Harris et al (2019) &lt;doi:10.1016/j.jbi.2019.103208&gt;).">
 <meta property="og:image" content="/logo.png">
 <!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 43fa87c..de11fc1 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: 2023-06-02T12:29Z
+last_built: 2023-06-05T06:39Z
 
diff --git a/docs/reference/REDCap_split.html b/docs/reference/REDCap_split.html
index b39fc45..1f72c7d 100644
--- a/docs/reference/REDCap_split.html
+++ b/docs/reference/REDCap_split.html
@@ -156,17 +156,19 @@ instruments only or for all forms.</p></dd>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># You must set the working directory first since the REDCap data export</span></span></span>
 <span class="r-in"><span><span class="co"># script contains relative file references.</span></span></span>
+<span class="r-in"><span><span class="va">old</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/getwd.html" class="external-link">getwd</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/getwd.html" class="external-link">setwd</a></span><span class="op">(</span><span class="st">"/path/to/data/"</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Run the data export script supplied by REDCap.</span></span></span>
 <span class="r-in"><span><span class="co"># This will create a data.frame of your records called 'data'</span></span></span>
 <span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/source.html" class="external-link">source</a></span><span class="op">(</span><span class="st">"ExampleProject_R_2018-06-03_1700.r"</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># Get the metadata</span></span></span>
+<span class="r-in"><span><span class="co"># Get the metadatan</span></span></span>
 <span class="r-in"><span><span class="va">metadata</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/utils/read.table.html" class="external-link">read.csv</a></span><span class="op">(</span><span class="st">"ExampleProject_DataDictionary_2018-06-03.csv"</span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Split the tables</span></span></span>
 <span class="r-in"><span><span class="fu">REDCapRITS</span><span class="fu">::</span><span class="fu">REDCap_split</span><span class="op">(</span><span class="va">data</span>, <span class="va">metadata</span><span class="op">)</span></span></span>
+<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/getwd.html" class="external-link">setwd</a></span><span class="op">(</span><span class="va">old</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 </code></pre></div>
     </div>
diff --git a/docs/search.json b/docs/search.json
index 62050f9..c3ebb3a 100644
--- a/docs/search.json
+++ b/docs/search.json
@@ -1 +1 @@
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Regardless server hosts Corresponding Source, remain obligated ensure available long needed satisfy requirements. e) Convey object code using peer--peer transmission, provided inform peers object code Corresponding Source work offered general public charge subsection 6d. separable portion object code, whose source code excluded Corresponding Source System Library, need included conveying object code work. “User Product” either (1) “consumer product”, means tangible personal property normally used personal, family, household purposes, (2) anything designed sold incorporation dwelling. determining whether product consumer product, doubtful cases shall resolved favor coverage. particular product received particular user, “normally used” refers typical common use class product, regardless status particular user way particular user actually uses, expects expected use, product. product consumer product regardless whether product substantial commercial, industrial non-consumer uses, unless uses represent significant mode use product. “Installation Information” User Product means methods, procedures, authorization keys, information required install execute modified versions covered work User Product modified version Corresponding Source. information must suffice ensure continued functioning modified object code case prevented interfered solely modification made. convey object code work section , , specifically use , User Product, conveying occurs part transaction right possession use User Product transferred recipient perpetuity fixed term (regardless transaction characterized), Corresponding Source conveyed section must accompanied Installation Information. requirement apply neither third party retains ability install modified object code User Product (example, work installed ROM). requirement provide Installation Information include requirement continue provide support service, warranty, updates work modified installed recipient, User Product modified installed. 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Additional permissions applicable entire Program shall treated though included License, extent valid applicable law. additional permissions apply part Program, part may used separately permissions, entire Program remains governed License without regard additional permissions. convey copy covered work, may option remove additional permissions copy, part . (Additional permissions may written require removal certain cases modify work.) may place additional permissions material, added covered work, can give appropriate copyright permission. Notwithstanding provision License, material add covered work, may (authorized copyright holders material) supplement terms License terms: ) Disclaiming warranty limiting liability differently terms sections 15 16 License; b) Requiring preservation specified reasonable legal notices author attributions material Appropriate Legal Notices displayed works containing ; c) Prohibiting misrepresentation origin material, requiring modified versions material marked reasonable ways different original version; d) Limiting use publicity purposes names licensors authors material; e) Declining grant rights trademark law use trade names, trademarks, service marks; f) Requiring indemnification licensors authors material anyone conveys material (modified versions ) contractual assumptions liability recipient, liability contractual assumptions directly impose licensors authors. non-permissive additional terms considered “restrictions” within meaning section 10. 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Program specifies certain numbered version GNU General Public License “later version” applies , option following terms conditions either numbered version later version published Free Software Foundation. Program specify version number GNU General Public License, may choose version ever published Free Software Foundation. Program specifies proxy can decide future versions GNU General Public License can used, proxy’s public statement acceptance version permanently authorizes choose version Program. Later license versions may give additional different permissions. However, additional obligations imposed author copyright holder result choosing follow later version.","code":""},{"path":"/LICENSE.html","id":"id_15-disclaimer-of-warranty","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"15. Disclaimer of Warranty","title":"GNU General Public License","text":"WARRANTY PROGRAM, EXTENT PERMITTED APPLICABLE LAW. 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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 <http://www.gnu.org/philosophy/--lgpl.html>.","code":"<one line to give the program's name and a brief idea of what it does.> Copyright (C) <year>  <name of author>  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 <http://www.gnu.org/licenses/>. <program>  Copyright (C) <year>  <name of author> 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 <-   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 23.6.1, 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 23.6.1},   url = {https://github.com/agdamsbo/REDCapCAST}, }"},{"path":"/index.html","id":"redcapcast-package-","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":"future","dir":"","previous_headings":"","what":"Future","title":"REDCap Castellated Data Handling","text":"plan package bundled Handbook working REDCap R. plan also include functionality assist casting (yes, pun intended) initial REDCap database.","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-23-6-1","dir":"Changelog","previous_headings":"","what":"Documentation:","title":"REDCapCAST 23.6.1","text":"Updated description. Look! hex icon! Heading CRAN.","code":""},{"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":""}]
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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 23.6.1, 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 23.6.1},   url = {https://github.com/agdamsbo/REDCapCAST}, }"},{"path":"/index.html","id":"redcapcast-package-","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":"future","dir":"","previous_headings":"","what":"Future","title":"REDCap Castellated Data Handling","text":"plan package bundled Handbook working REDCap R. plan also include functionality assist casting (yes, pun intended) initial REDCap database.","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. old <- getwd() 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 metadatan metadata <- read.csv(\"ExampleProject_DataDictionary_2018-06-03.csv\")  # Split the tables REDCapRITS::REDCap_split(data, metadata) setwd(old) }"},{"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-23-6-1","dir":"Changelog","previous_headings":"","what":"Documentation:","title":"REDCapCAST 23.6.1","text":"Updated description. Look! hex icon! Heading CRAN.","code":""},{"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/inst/WORDLIST b/inst/WORDLIST
index 76482b3..505c062 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -12,12 +12,14 @@ REDCap
 REDCapR
 REDCapRITS
 SpectrumHealthResearch
+al
 api
 demonstrational
 descirption
 desireable
 doi
 dplyr
+et
 immprovements
 jbi
 mRS
@@ -28,44 +30,3 @@ og
 thorugh
 tidyverse
 uri
-agdamsbo
-Andreas
-au
-aut
-BugReports
-clin
-covr
-cre
-Damsbo
-dk
-doi
-dplyr
-egeler
-Egeler
-Gammelgaard
-github
-Hmisc
-https
-httr
-jbi
-jsonlite
-keyring
-knitr
-LazyData
-ORCID
-paul
-RCurl
-readr
-REDCap,49
-redcapcast
-REDCapCAST
-REDCapR
-REDCapRITS
-rmarkdown
-RoxygenNote
-spectrumhealth
-SpectrumHealthResearch
-testthat
-tidyr
-tidyselect
-VignetteBuilder
diff --git a/man/REDCap_split.Rd b/man/REDCap_split.Rd
index 7551d84..eac982b 100644
--- a/man/REDCap_split.Rd
+++ b/man/REDCap_split.Rd
@@ -84,17 +84,19 @@ REDCapRITS::REDCap_split(records, metadata)
 
 # You must set the working directory first since the REDCap data export
 # script contains relative file references.
+old <- getwd()
 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
+# Get the metadatan
 metadata <- read.csv("ExampleProject_DataDictionary_2018-06-03.csv")
 
 # Split the tables
 REDCapRITS::REDCap_split(data, metadata)
+setwd(old)
 }
 }
 \author{