Creates a forest plot displaying individual study effects and pooled estimate from a meta-analysis.
Usage
create_meta_forest_plot(
meta_result,
title = NULL,
xlab = NULL,
show_weights = TRUE,
show_heterogeneity = TRUE,
show_prediction = TRUE,
null_value = NULL,
xlim = NULL,
palette = NULL,
base_size = 11
)Arguments
- meta_result
A MetaResult object from meta_analysis()
- title
Character. Plot title. Default: NULL
- xlab
Character. X-axis label. Default: based on effect_measure
- show_weights
Logical. Show study weights. Default: TRUE
- show_heterogeneity
Logical. Show heterogeneity stats. Default: TRUE
- show_prediction
Logical. Show prediction interval. Default: TRUE
- null_value
Numeric. Reference line value. Default: 1 for ratios, 0 for differences
- xlim
Numeric vector. X-axis limits. Default: NULL (auto)
- palette
Character vector. Colors. Default: NULL
- base_size
Numeric. Base font size. Default: 11
Examples
# Meta-analysis forest plot
yi <- log(c(0.75, 0.82, 0.68, 0.91))
sei <- c(0.12, 0.15, 0.18, 0.14)
result <- meta_analysis(
yi = yi, sei = sei,
study_labels = c("Study A", "Study B", "Study C", "Study D"),
effect_measure = "hr"
)
plot <- create_meta_forest_plot(result, title = "Treatment Effect")
plot@type
#> [1] "forest_meta"