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[{"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. <http://fsf.org/> 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 23.6.1, 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":""}]
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