Conduct KDA regression analysis

A short description...

Usage

kda_regression(
  data = NULL,
  outcome = NULL,
  predictors = NULL,
  model = NULL,
  diagnostics = FALSE,
  importance_method = "auto",
  importance_barPlot_args = list(),
  performance_barPlot_args = list(),
  ipma_scatterPlot_args = list()
)

Arguments

data

A data frame containing the outcome and predictors. Optional if model is provided.

outcome

A single string naming the outcome variable. Optional if model is provided.

predictors

A character vector of predictor variable names. Optional if model is provided.

model

A fitted regression model object. Optional if data, outcome, and predictors are provided.

diagnostics

A logical indicating whether to compute model diagnostics. Defaults to FALSE. If TRUE, see here for interpretation and possible solutions.

importance_method

One of "auto", "domir", "jrw", or "sumOfCoefficients". Defaults to "auto".

importance_barPlot_args

Optional. A list of additional arguments passed to the importance bar plot function. See kda_importance_barPlot() for details..

performance_barPlot_args

Optional. A list of additional arguments passed to the performance bar plot function. See kda_performance_barPlot() for details..

ipma_scatterPlot_args

Optional. A list of additional arguments passed to the IPMA scatter plot function. See kda_ipma_scatterPlot() for details..

Value

A list containing model results, importance measures, performance metrics, IPMA analysis, and associated plots. Errors if neither model nor all of data, outcome, and predictors are provided.