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

 ```1 2 3 4 5 6 7 8 9``` ```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

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