Suggest Clinical Variables for Formula Construction — suggest_clinical

Automatically detects likely CDISC variables in a dataset and suggests appropriate formula syntax for longitudinal plotting.

Usage

suggest_clinical_vars(data, verbose = TRUE)

Arguments

data: A data frame containing clinical trial data.
verbose: Logical. If TRUE, provides detailed suggestions and warnings.

Value

A list containing:

suggested_formula: Recommended formula for lplot
detected_vars: List of detected CDISC variables by category
cluster_var: Recommended cluster variable (subject ID)
baseline_value: Detected baseline visit value
warnings: Any data quality or compliance issues

Examples

# Clinical trial dataset
clinical_data <- data.frame(
  USUBJID = paste0("001-", 1:20),
  AVISITN = rep(c(0, 1, 2, 3), 5),
  AVAL = rnorm(20),
  TRT01P = rep(c("Placebo", "Active"), 10)
)

suggestions <- suggest_clinical_vars(clinical_data)
#> CDISC Variable Detection Results:
#> =================================
#> 
#> Suggested Formula: AVAL ~ AVISITN | TRT01P 
#> Cluster Variable: USUBJID 
#> Baseline Value: 0 
#> 
#> Detected Variables:
#>   subject_id: USUBJID
#>   visit: AVISITN
#>   analysis_value: AVAL
#>   treatment: TRT01P
#> 
#> Warnings:
#>   ! Dataset appears to have limited longitudinal data (< 2 observations per subject).
#>   ! No population analysis flags detected. Consider adding SAFFL, FASFL.
#> 
print(suggestions$suggested_formula)
#> [1] "AVAL ~ AVISITN | TRT01P"