Visualise convergence diagnostics — vismi

This function generates convergence diagnostic plots showing the mean and standard deviation (SD) of imputed values for a specified variable across iterations.

Usage

vismi_converge(
  obj,
  x,
  xlim = NULL,
  mean_lim = NULL,
  sd_lim = NULL,
  title = "auto",
  subtitle = "auto",
  tick_vals = NULL,
  color_pal = NULL,
  linewidth = 0.8,
  ...
)

Arguments

obj: A 'mixgb' object returned by mixgb() function or a 'mids' object returned by the mice() function.
x: The name of the variable to plot convergence for.
xlim: Optional numeric vector of length 2 specifying the x-axis limits for iterations.
mean_lim: Optional numeric vector of length 2 specifying the y-axis limits for mean values of the variable.
sd_lim: Optional numeric vector of length 2 specifying the y-axis limits for standard deviation values of the variable.
title: A string specifying the title of the plot. If NULL, no title is shown. If "auto", a title will be generated based on the input. Default is "auto".
subtitle: A string specifying the subtitle of the plot. If NULL, no subtitle is shown. If "auto", a title will be generated based on the input. Default is "auto".
tick_vals: Optional numeric vector specifying x-axis tick values for iterations.
color_pal: A vector of m color codes (e.g., hex codes). If NULL, default colors will be used.
linewidth: The line width for the plot lines. Default is 0.8.
...: Additional arguments.

Value

Two side-by-side ggplot2 object showing the mean and standard deviation (SD) of imputed values for a specified variable across iterations.

Examples

library(mixgb)
set.seed(2026)
mixgb_obj <- mixgb(data = nhanes3, m = 3, maxit = 4, pmm.type = "auto", save.models = TRUE)
vismi_converge(obj = mixgb_obj, x = "recumbent_length_cm")