Dynamic Sequential Multivariable Logistic Regression — run_multivariable_logistic

Fits cumulative multivariable logistic regression models across N-layers defined by models_list. The function ensures reference categories (1.00 (Ref)) are consistently maintained and horizontally aligned across all adjustment levels.

Usage

run_multivariable_logistic_regression(
  data,
  outcomes,
  predictors,
  models_list,
  outcomes_map = NULL,
  predictors_map = NULL,
  output_dir = NULL,
  save_format = c("none", "docx", "csv", "txt")
)

Arguments

data: A data frame containing the variables.
outcomes: Character vector of outcome variable names (Binary).
predictors: Character vector of primary predictors to be evaluated.
models_list: A NAMED list where each element contains new covariates to be added sequentially (e.g., list(Base = c("age"), Clinical = c("nodes"))).
outcomes_map: Optional named mapping for outcome display labels.
predictors_map: Optional named mapping for predictor display labels.
output_dir: Optional path to save output files.
save_format: Save format: "none", "docx", "csv", or "txt".

Value

A list containing a consolidated results data frame and saved file paths.

Examples

if (FALSE) { # \dontrun{
library(survival)
data(colon)
df <- colon %>% dplyr::filter(etype == 2) %>% dplyr::mutate(status = as.factor(status))

models <- list(
  "Demographics" = c("age", "sex"),
  "Pathology"    = c("nodes", "extent")
)

run_multivariable_logistic_regression(
  data = df,
  outcomes = "status",
  predictors = "adhere",
  models_list = models,
  save_format = "docx"
)
} # }