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Wrapper on choices_labeled to label variable values basing on other variable values

value_choices.Rd

[Stable]

Usage

value_choices(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")

# S3 method for character
value_choices(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")

# S3 method for data.frame
value_choices(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")

# S3 method for TealDataset
value_choices(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")

# S3 method for TealDatasetConnector
value_choices(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")

Arguments

data

(data.frame, character, TealDataset, TealDatasetConnector) If data.frame, then data to extract labels from If character, then name of the dataset to extract data from once available If TealDataset or TealDatasetConnector, then raw data to extract labels from.

var_choices

(character or NULL) vector with choices column names

var_label

(character) vector with labels column names

subset

(character or function) If character, vector with values to subset. If function, then this function is used to determine the possible columns (e.g. all factor columns). In this case, the function must take only single argument "data" and return a character vector. See examples for more details.

sep

(character) separator used in case of multiple column names

Value

named character vector or delayed_data object

Examples

library(scda)
ADRS <- synthetic_cdisc_data("latest")$adrs

value_choices(ADRS, "PARAMCD", "PARAM", subset = c("BESRSPI", "INVET"))
#> number of choices: 2 
#> 
#> BESRSPI: Best Confirmed Overall Response by Investigator
#> INVET: Investigator End Of Induction Response
#> 
value_choices(ADRS, c("PARAMCD", "ARMCD"), c("PARAM", "ARM"))
#> number of choices: 9 
#> 
#> BESRSPI - ARM A: Best Confirmed Overall Response by Investigator - A: Drug X
#> INVET - ARM A: Investigator End Of Induction Response - A: Drug X
#> OVRINV - ARM A: Overall Response by Investigator - by visit - A: Drug X
#> BESRSPI - ARM C: Best Confirmed Overall Response by Investigator - C: Combination
#> INVET - ARM C: Investigator End Of Induction Response - C: Combination
#> OVRINV - ARM C: Overall Response by Investigator - by visit - C: Combination
#> BESRSPI - ARM B: Best Confirmed Overall Response by Investigator - B: Placebo
#> INVET - ARM B: Investigator End Of Induction Response - B: Placebo
#> OVRINV - ARM B: Overall Response by Investigator - by visit - B: Placebo
#> 
value_choices(ADRS, c("PARAMCD", "ARMCD"), c("PARAM", "ARM"),
  subset = c("BESRSPI - ARM A", "INVET - ARM A", "OVRINV - ARM A")
)
#> number of choices: 3 
#> 
#> BESRSPI - ARM A: Best Confirmed Overall Response by Investigator - A: Drug X
#> INVET - ARM A: Investigator End Of Induction Response - A: Drug X
#> OVRINV - ARM A: Overall Response by Investigator - by visit - A: Drug X
#> 
value_choices(ADRS, c("PARAMCD", "ARMCD"), c("PARAM", "ARM"), sep = " --- ")
#> number of choices: 9 
#> 
#> BESRSPI --- ARM A: Best Confirmed Overall Response by Investigator --- A: Drug X
#> INVET --- ARM A: Investigator End Of Induction Response --- A: Drug X
#> OVRINV --- ARM A: Overall Response by Investigator - by visit --- A: Drug X
#> BESRSPI --- ARM C: Best Confirmed Overall Response by Investigator --- C: Combination
#> INVET --- ARM C: Investigator End Of Induction Response --- C: Combination
#> OVRINV --- ARM C: Overall Response by Investigator - by visit --- C: Combination
#> BESRSPI --- ARM B: Best Confirmed Overall Response by Investigator --- B: Placebo
#> INVET --- ARM B: Investigator End Of Induction Response --- B: Placebo
#> OVRINV --- ARM B: Overall Response by Investigator - by visit --- B: Placebo
#> 

# delayed version
value_choices("ADRS", c("PARAMCD", "ARMCD"), c("PARAM", "ARM"))
#> value_choices with delayed data:  ADRS
#> $ data
#> [1] "ADRS"
#> $ var_choices
#> [1] "PARAMCD" "ARMCD"  
#> $ var_label
#> [1] "PARAM" "ARM"  
#> $ subset
#> NULL
#> $ sep
#> [1] " - "

# functional subset
value_choices(ADRS, "PARAMCD", "PARAM", subset = function(data) {
  return(levels(data$PARAMCD)[1:2])
})
#> number of choices: 2 
#> 
#> BESRSPI: Best Confirmed Overall Response by Investigator
#> INVET: Investigator End Of Induction Response
#>