Generate a metric vs drift table

Usage

table_metric_vs_drift(
  metric,
  results_metrics_df,
  theta_0,
  case_study,
  method,
  category,
  control_drift,
  target_sample_size_per_arm,
  parameters_combinations,
  xvars,
  source_denominator_change_factor = 1,
  target_to_source_std_ratio = 1,
  wide_table = TRUE
)

Arguments

metric: The metric to be plotted
results_metrics_df: A dataframe containing the results metrics
theta_0: The null hypothesis value
case_study: The case study being analyzed
method: The method being used
category: The category of analysis ('parameters' or 'target_sample_size_per_arm')
control_drift: Boolean indicating whether to control for drift
target_sample_size_per_arm: The target sample size per arm
parameters_combinations: The combinations of parameters
xvars: A list containing x-axis variable information
source_denominator_change_factor: The source denominator change factor of the scenario to keep.
target_to_source_std_ratio: Ratio between the target and source studies sampling standard deviation.
wide_table: Whether to pivot the table so that each parameter combination gets its own column.

Value

Generates and saves tables in HTML, PDF, and LaTeX formats