weighted_mean_effect_size: Estimate the mean effect size in a meta analysis

In kim: A Toolkit for Behavioral Scientists

Estimate the mean effect size in a meta analysis

Description

Estimate the mean effect size in a meta analysis, as illustrated in Borenstein et al. (2009, pp. 73-74, ISBN: 978-0-470-05724-7)

Usage

weighted_mean_effect_size(
  effect_sizes = NULL,
  effect_size_variances = NULL,
  ci = 0.95,
  one_tailed = FALSE,
  random_vs_fixed = "random"
)

Arguments

effect_sizes	effect sizes (e.g., standardized mean differences)
effect_size_variances	within-study variances
ci	width of the confidence interval (default = 0.95)
one_tailed	logical. If one_tailed = FALSE, a two-tailed p-value will be calculated. If one_tailed = TRUE, a one-tailed p-value will be calculated (default = FALSE)
random_vs_fixed	If random_vs_fixed = "random", the summary effect will be calculated under the random-effects model (default = "random").

Examples

## Not run: 
weighted_mean_effect_size(
effect_sizes = c(1, 2), effect_size_variances = c(3, 4))
weighted_mean_effect_size(
effect_sizes = c(0.095, 0.277, 0.367, 0.664, 0.462, 0.185),
effect_size_variances = c(0.033, 0.031, 0.050, 0.011, 0.043, 0.023))
# if effect sizes have a variance of 0, they will be excluded from
# the analysis
weighted_mean_effect_size(
effect_sizes = c(1.1, 1.2, 1.3, 1.4),
effect_size_variances = c(1, 0, 0, 4))

## End(Not run)

kim documentation built on Oct. 9, 2023, 5:08 p.m.