forest_cont_subgroup: Forest Plot for Subgroup Meta-Analysis

Description

Creates a detailed forest plot for subgroup meta-analysis, including study-level effect sizes, subgroup pooled effects, heterogeneity statistics, overall pooled effect, and prediction intervals.

Usage

forest_cont_subgroup(
  dat,
  m_t_col = "mean_t",
  sd_t_col = "sd_t",
  n_t_col = "n_t",
  m_c_col = "mean_c",
  sd_c_col = "sd_c",
  n_c_col = "n_c",
  subgroup_col = "subgroup",
  study_col = "Study",
  measure = "SMD",
  method = "REML",
  xlab = NULL,
  xlim = NULL,
  model = "RE",
  title = "Subgroup Forest Plot",
  diamond.col = "red",
  overall.col = "darkgreen",
  study.col = "blue",
  CI.col = "blue",
  Pred.Inter.col = "black",
  square.size = 5,
  Pred.Int.size = 1.5,
  text_size = 3.5,
  pred = TRUE,
  xpos = list(Study = NULL, MeanT = NULL, MeanC = NULL, Effect = NULL, Weight = NULL,
    PredInt = NULL, Hetero = NULL)
)

Value

A ggplot object representing the subgroup forest plot.

Arguments

dat: A data frame containing the study-level data. Use dat1 included in the package for examples.
m_t_col: Name of the column for treatment group means.
sd_t_col: Name of the column for treatment group standard deviations.
n_t_col: Name of the column for treatment group sample sizes.
m_c_col: Name of the column for control group means.
sd_c_col: Name of the column for control group standard deviations.
n_c_col: Name of the column for control group sample sizes.
subgroup_col: Name of the column indicating subgroup membership.
study_col: Name of the column with study labels.
measure: Effect size measure: "SMD" (standardized mean difference) or "MD" (mean difference).
method: Method for meta-analysis: "REML" (default) or "FE".
xlab: Label for the x-axis.
xlim: Limits for the x-axis as a numeric vector of length 2.
model: Random-effects ("RE") or fixed-effects ("FE") model for pooled estimates.
title: Plot title.
diamond.col: Color for subgroup pooled effect diamonds.
overall.col: Color for the overall pooled effect diamond.
study.col: Color for study-level points.
CI.col: Color for confidence intervals of individual studies.
Pred.Inter.col: Color for the overall prediction interval.
square.size: Maximum size of study-level effect squares.
Pred.Int.size: Line thickness for prediction interval.
text_size: Base text size for annotations.
pred: Logical; if TRUE, display overall prediction interval.
xpos: numeric vector of x-axis positions for annotations

Examples

Run this code

# Using the built-in dataset dat1
forest_cont_subgroup(dat1)

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