mod_power: Compute Power for Categorical Moderator Analysis in...

In metapower: Power Analysis for Meta-Analysis

Description

Computes statistical power for categorical moderator analysis under fixed and random effects models.

Usage

mod_power(
  n_groups,
  effect_sizes,
  study_size,
  k,
  i2,
  es_type,
  p = 0.05,
  con_table = NULL
)

Arguments

n_groups	Numerical value for the levels of a categorical variable.
effect_sizes	Numerical values for effect sizes of for each group.
study_size	Numerical value for number of participants (per study).
k	Numerical value for total number of studies.
i2	Numerical value for Heterogeneity estimate (i^2).
es_type	Character reflecting effect size metric: 'r', 'd', or 'or'.
p	Numerical value for significance level (Type I error probability).
con_table	(Optional) List of numerical values for 2x2 contingency tables as a vector in the following format: c(a,b,c,d). These should be specified for each group(i.e., n_groups). 2x2 Table Group 1 Group 2 Present a b Not Present c d

Value

Estimated Power estimates for moderator analysis under fixed- and random-effects models

See Also

https://jason-griffin.shinyapps.io/shiny_metapower/

Examples

mod_power(n_groups = 2,
          effect_sizes = c(.1,.5),
          study_size = 20,
          k = 10,
          i2 = .50,
          es_type = "d")
mod_power(n_groups = 2,
          con_table = list(g1 = c(6,5,4,5), g2 = c(8,5,2,5)),
          study_size = 40,
          k = 20,
          i2 = .50,
          es_type = "or")

metapower documentation built on Feb. 8, 2021, 5:07 p.m.