REDCapCAST/docs/search.json

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R package version 23.3.2, https://github.com/agdamsbo/REDCapRITS.","code":"@Manual{,   title = {REDCapCAST: REDCap Castellated data handling},   author = {Paul Egeler},   year = {2023},   note = {R package version 23.3.2},   url = {https://github.com/agdamsbo/REDCapRITS}, }"},{"path":"/index.html","id":"redcapcast","dir":"","previous_headings":"","what":"REDCap Castellated data handling","title":"REDCap Castellated data handling","text":"REDCap Castellated data handling using repeated instruments. Modified fork SpectrumHealthResearch/REDCapRITS. fork purely minded R usage includes implementations main REDCap_split function. Fork REDCapRITS: REDCap Repeating Instrument Table Splitter","code":""},{"path":"/reference/REDCap_split.html","id":null,"dir":"Reference","previous_headings":"","what":"Split REDCap repeating instruments table into multiple tables — REDCap_split","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"take output REDCap export split base table child tables repeating instrument. Metadata used determine fields included resultant table.","code":""},{"path":"/reference/REDCap_split.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"","code":"REDCap_split(   records,   metadata,   primary_table_name = \"\",   forms = c(\"repeating\", \"all\") )"},{"path":"/reference/REDCap_split.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"records Exported project records. May data.frame, response, character vector containing JSON API call. metadata Project metadata (data dictionary). May data.frame, response, character vector containing JSON API call. primary_table_name Name given list element primary output table (described README.md). Ignored forms = ''. forms Indicate whether create separate tables repeating instruments forms.","code":""},{"path":"/reference/REDCap_split.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"list \"data.frame\"s. number tables differ   depending forms option selected.  'repeating': one base table one     tables repeating instrument. '': data.frame instrument, regardless     whether repeating instrument .","code":""},{"path":"/reference/REDCap_split.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"Paul W. Egeler, M.S., GStat","code":""},{"path":"/reference/REDCap_split.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split REDCap repeating instruments table into multiple tables — REDCap_split","text":"","code":"if (FALSE) { # Using an API call -------------------------------------------------------  library(RCurl)  # Get the records records <- postForm(   uri = api_url,     # Supply your site-specific URI   token = api_token, # Supply your own API token   content = 'record',   format = 'json',   returnFormat = 'json' )  # Get the metadata metadata <- postForm(   uri = api_url,     # Supply your site-specific URI   token = api_token, # Supply your own API token   content = 'metadata',   format = 'json' )  # Convert exported JSON strings into a list of data.frames REDCapRITS::REDCap_split(records, metadata)  # Using a raw data export -------------------------------------------------  # Get the records records <- read.csv(\"/path/to/data/ExampleProject_DATA_2018-06-03_1700.csv\")  # Get the metadata metadata <- read.csv(\"/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv\")  # Split the tables REDCapRITS::REDCap_split(records, metadata)  # In conjunction with the R export script ---------------------------------  # You must set the working directory first since the REDCap data export script # contains relative file references. setwd(\"/path/to/data/\")  # Run the data export script supplied by REDCap. # This will create a data.frame of your records called 'data' source(\"ExampleProject_R_2018-06-03_1700.r\")  # Get the metadata metadata <- read.csv(\"ExampleProject_DataDictionary_2018-06-03.csv\")  # Split the tables REDCapRITS::REDCap_split(data, metadata) }"},{"path":"/reference/focused_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"focused_metadata — focused_metadata","title":"focused_metadata — focused_metadata","text":"Extracts limited metadata variables dataset","code":""},{"path":"/reference/focused_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"focused_metadata — focused_metadata","text":"","code":"focused_metadata(metadata, vars_in_data)"},{"path":"/reference/focused_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"focused_metadata — focused_metadata","text":"metadata dataframe containing metadata vars_in_data Vector variable names dataset","code":""},{"path":"/reference/focused_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"focused_metadata — focused_metadata","text":"dataframe containing metadata variables dataset","code":""},{"path":"/reference/match_fields_to_form.html","id":null,"dir":"Reference","previous_headings":"","what":"Match fields to forms — match_fields_to_form","title":"Match fields to forms — match_fields_to_form","text":"Match fields forms","code":""},{"path":"/reference/match_fields_to_form.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Match fields to forms — match_fields_to_form","text":"","code":"match_fields_to_form(metadata, vars_in_data)"},{"path":"/reference/match_fields_to_form.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Match fields to forms — match_fields_to_form","text":"metadata data frame containing field names form names vars_in_data character vector variable names","code":""},{"path":"/reference/match_fields_to_form.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Match fields to forms — match_fields_to_form","text":"data frame containing field names form names","code":""},{"path":"/reference/read_redcap_tables.html","id":null,"dir":"Reference","previous_headings":"","what":"Download REDCap data — read_redcap_tables","title":"Download REDCap data — read_redcap_tables","text":"Implementation REDCap_split focused data acquisition approach using REDCapR::redcap_read nad downloading specified fields, forms /events using built-focused_metadata including clean-. Works longitudinal projects repeating instruments.","code":""},{"path":"/reference/read_redcap_tables.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download REDCap data — read_redcap_tables","text":"","code":"read_redcap_tables(   uri,   token,   records = NULL,   fields = NULL,   events = NULL,   forms = NULL,   raw_or_label = \"label\",   split_forms = \"all\",   generics = c(\"record_id\", \"redcap_event_name\", \"redcap_repeat_instrument\",     \"redcap_repeat_instance\") )"},{"path":"/reference/read_redcap_tables.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download REDCap data — read_redcap_tables","text":"uri REDCap database uri token API token records records download fields fields download events events download forms forms download raw_or_label raw label tags split_forms Whether split \"repeating\" \"\" forms, default . generics vector auto-generated generic variable names ignore discarding empty rows","code":""},{"path":"/reference/read_redcap_tables.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download REDCap data — read_redcap_tables","text":"list instruments","code":""},{"path":"/reference/read_redcap_tables.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download REDCap data — read_redcap_tables","text":"","code":"# Examples will be provided later"},{"path":"/reference/redcap_wider.html","id":null,"dir":"Reference","previous_headings":"","what":"Redcap Wider — redcap_wider","title":"Redcap Wider — redcap_wider","text":"Converts list REDCap data frames long wide format. Handles longitudinal projects, yet repeated instruments.","code":""},{"path":"/reference/redcap_wider.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Redcap Wider — redcap_wider","text":"","code":"redcap_wider(   list,   event.glue = \"{.value}_{redcap_event_name}\",   inst.glue = \"{.value}_{redcap_repeat_instance}\" )"},{"path":"/reference/redcap_wider.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Redcap Wider — redcap_wider","text":"list list data frames. event.glue dplyr::glue string repeated events naming inst.glue dplyr::glue string repeated instruments naming","code":""},{"path":"/reference/redcap_wider.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Redcap Wider — redcap_wider","text":"list data frames wide format.","code":""},{"path":"/reference/redcap_wider.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Redcap Wider — redcap_wider","text":"","code":"list <- list(data.frame(record_id = c(1,2,1,2), redcap_event_name = c(\"baseline\", \"baseline\", \"followup\", \"followup\"), age = c(25,26,27,28)), data.frame(record_id = c(1,2), redcap_event_name = c(\"baseline\", \"baseline\"), gender = c(\"male\", \"female\"))) redcap_wider(list) #> Joining with `by = join_by(record_id)` #>   record_id age_baseline age_followup gender #> 1         1           25           27   male #> 2         2           26           28 female"},{"path":"/reference/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-23-3-2","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":""}]