This function generates a matrix of statistical relationships between specified outcome and predictor variables in a dataset. It includes visualizations for correlations, ANOVA results, and FDR corrections.
Usage
PlotMiningMatrix(
Data,
OutcomeVars,
PredictorVars,
Covariates = NULL,
Relabel = TRUE,
Parametric = TRUE
)Arguments
- Data
A data frame containing the dataset to analyze.
- OutcomeVars
A vector of outcome variables to be analyzed.
- PredictorVars
A vector of predictor variables to be analyzed.
- Covariates
An optional vector of covariates to adjust the analysis (default is NULL).
- Relabel
Logical flag indicating whether to relabel the variables in the output (default is TRUE).
- Parametric
Logical flag indicating whether to use parametric methods (default is TRUE). If FALSE, non-parametric methods will be used.
Value
A list containing the following elements:
- Unadjusted
A list with the unadjusted p-value table and corresponding plot.
- FDRCorrected
A list with the FDR-adjusted p-value table and corresponding plot.
- method
The method used for correlation ("pearson" for parametric, "spearman" for non-parametric).
- Relabel
The value of the Relabel parameter.
- Covariates
The covariates used in the analysis, if any.