## Changes

- For all major functions, the input parameter i2 should now be specified by the user (i2 = .5 by default)
- All plotting functions plot power curves as a function of model selection (fixed or random effects)

## Update

### Changes

- For random-effects models, mpower() now uses a different formula to account for uncertainty in \(\tau^2\) (see Jackson & Turner, 2017)
- All plot functions were changes to have a preceding plot_. For example:
`plot_mpower()`

; `plot_homogen_power()`

; `plot_subgroup_power()`

; `plot_mod_power`

### Additions

- Added subgroup_power(), which computes power to detect differences in subgroups among studies (i.e., Men vs Women)
- The subgroup_power() has slightly different arguments to allow more flexibility, especially for Odds Ratio
- Added a plotting function to subgroup_power() called plot_subgroup_power
- A fully functional shiny application is now available (https://jason-griffin.shinyapps.io/shiny_metapower/)

## New Release

### Primary functions

- mpower(): Compute statistical power for meta-analysis
- mod_power(): Compute power for categorical moderator meta-analytic models
- power_plot(): Visualize a range of power curves
- homogen_power_plot(): visualize a range of power curves for the test of homogeneity