plot_funnel: Create funnel plots

In psychmeta/psychmeta: Psychometric Meta-Analysis Toolkit

Create funnel plots

Description

This function creates funnel plots for meta-analyses (plots of effect size versus standard error).

Usage

plot_funnel(
  ma_obj,
  se_type = c("auto", "mean", "sample"),
  label_es = NULL,
  conf_level = c(0.95, 0.99),
  conf_linetype = c("dashed", "dotted"),
  conf_fill = NA,
  conf_alpha = 1,
  null_effect = NA,
  null_conf_level = c(0.9, 0.95, 0.99),
  null_conf_linetype = c("solid", "dashed", "dotted"),
  null_conf_fill = "black",
  null_conf_alpha = c(0.1, 0.2, 0.4),
  analyses = "all",
  match = c("all", "any"),
  case_sensitive = TRUE,
  show_filtered = FALSE
)

plot_cefp(
  ma_obj,
  se_type = "sample",
  label_es = NULL,
  conf_level = NA,
  conf_linetype = NA,
  conf_fill = NA,
  conf_alpha = 1,
  null_effect = NULL,
  null_conf_level = c(0.9, 0.95, 0.99),
  null_conf_linetype = c("solid", "dashed", "dotted"),
  null_conf_fill = "black",
  null_conf_alpha = c(0, 0.2, 0.4),
  analyses = "all",
  match = c("all", "any"),
  case_sensitive = TRUE,
  show_filtered = FALSE
)

Arguments

ma_obj	Meta-analysis object.
se_type	Method to calculate standard errors (y-axis). Options are "auto" (default) to use the same method as used to estimate the meta-analysis models, "mean" to calculate SEs using the mean effect size and indivdiual sample sizes, or '"sample"“ to use the SE calculated using the sample effect sizes and sample sizes.
label_es	Label for effect size (x-axis). Defaults to "Correlation (r)" for correlation meta-analyses, "Cohen's d (Hedges's g)" for d value meta-analyses, and "Effect size" for generic meta-analyses.
conf_level	Confidence regions levels to be plotted (default: .95, .99).
conf_linetype	Line types for confidence region boundaries. Length should be either 1 or equal to the length of conf_level.
conf_fill	Colors for confidence regions. Set to NA for transparent. Length should be either 1 or equal to to the length of conf_level.
conf_alpha	Transparency level for confidence regions. Length should be either 1 or equal to to the length of conf_level.
null_effect	Null effect to be plotted for contour-enhanced funnel plots. If NA, not shown. If NULL, set to the null value for the effect size metric (0 for correlations and d values).
null_conf_level	Null-effect confidence regions levels to be plotted (default: .90, .95, .99).
null_conf_linetype	Line types for null-effect confidence region boundaries. Length should be either 1 or equal to the length of null_conf_level.
null_conf_fill	Colors for null-effect confidence regions. Set to NA for transparent. Length should be either 1 or equal to the length of null_conf_level.
null_conf_alpha	Transparency level for null-effect confidence regions. Length should be either 1 or equal to the length of null_conf_level.
analyses	Which analyses to extract? Can be either "all" to extract references for all meta-analyses in the object (default) or a list containing arguments for filter_ma.
match	Should extracted meta-analyses match all (default) or any of the criteria given in analyses?
case_sensitive	Logical scalar that determines whether character values supplied in analyses should be treated as case sensitive (TRUE, default) or not (FALSE).
show_filtered	Logical scalar that determines whether the meta-analysis object given in the output should be the modified input object (FALSE, default) or the filtered object (TRUE).

Details

Both traditional funnel plots and contour-enhanced funnel plots are provided. Contour-enhanced funnel plots show comparison regions for varying null-hypothesis significance test levels and can be useful for detecting publication bias.

Value

A list of funnel plots.

Author(s)

Based on code by John Sakaluk

Examples

## Not run: 
## Correlations
ma_obj <- ma_r(ma_method = "ic", rxyi = rxyi, n = n, rxx = rxxi, ryy = ryyi,
               construct_x = x_name, construct_y = y_name, sample_id = sample_id,
               moderators = moderator, data = data_r_meas_multi)
plot_funnel(ma_obj = ma_obj)
plot_funnel(ma_obj = ma_obj, analyses = list(pair_id = 2))
plot_funnel(ma_obj = ma_obj, analyses = list(pair_id = 1, analysis_id = 1), show_filtered = TRUE)

## d values
ma_obj <- ma_d(ma_method = "ic", d = d, n1 = n1, n2 = n2, ryy = ryyi,
               construct_y = construct, sample_id = sample_id,
               data = data_d_meas_multi)
plot_funnel(ma_obj = ma_obj)
plot_funnel(ma_obj = ma_obj, analyses = list(pair_id = 2))
plot_funnel(ma_obj = ma_obj, analyses = list(pair_id = 1, analysis_id = 1), show_filtered = TRUE)

## End(Not run)

psychmeta/psychmeta documentation built on Feb. 12, 2024, 1:21 a.m.