homogen_power: Compute Power for Test of Homogeneity in Meta-analysis

In jasonwgriffin/metapower: Power Analysis for Meta-Analysis

Description

Compute statistical power for the Test of Homogeneity for meta-analysis under both fixed- and random-effects models.

Usage

homogen_power(
  effect_size,
  study_size,
  k,
  i2,
  es_type,
  p = 0.05,
  con_table = NULL
)

Arguments

effect_size	Numerical value of effect size.
study_size	Numerical value for number 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) Numerical values for 2x2 contingency table as a vector in the following format: c(a,b,c,d). 2x2 Table Group 1 Group 2 Present a b Not Present c d

Value

Estimated Power to detect differences in homogeneity of effect sizes for fixed- and random-effects models

References

Borenstein, M., Hedges, L. V., Higgins, J. P. T. and Rothstein, H. R.(2009). Introduction to meta-analysis, Chichester, UK: Wiley.

Hedges, L., Pigott, T. (2004). The Power of Statistical Tests for Moderators in Meta-Analysis, Psychological Methods, 9(4), 426-445. doi: https://dx.doi.org/10.1037/1082-989x.9.4.426

Pigott, T. (2012). Advances in Meta-Analysis. doi: https://dx.doi.org/10.1007/978-1-4614-2278-5

See Also

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

Examples

homogen_power(effect_size = .5, study_size = 10, k = 10, i2 = .50, es_type = "d")

jasonwgriffin/metapower documentation built on April 30, 2021, 10:09 a.m.