# morey_plot: Plot out power sensitivity plots for t or F tests In Superpower: Simulation-Based Power Analysis for Factorial Designs

## Description

Plot out power sensitivity plots for t or F tests

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```morey_plot.ttest( es = seq(0, 1, 0.05), n = NULL, type = c("two.sample", "one.sample", "paired"), alternative = c("two.sided", "one.sided"), alpha_level = Superpower_options("alpha_level") ) morey_plot.ftest( es = seq(0, 1, 0.05), num_df = 1, den_df = NULL, alpha_level = Superpower_options("alpha_level"), liberal_lambda = Superpower_options("liberal_lambda") ) ```

## Arguments

 `es` Effect size magnitudes to include on the plot; either cohen's f or cohen's d depending on whether it is an F-test or t-test `n` Sample size (t-test only) per group (two sample), total number of pairs (paired samples), or total observations (one-sample); only applies to t-test `type` string specifying the type of t test. Can be abbreviated. (t-test only) `alternative` one- or two-sided test. Can be abbreviated. (t-test only) `alpha_level` vector of alpha levels; default is 0.05 `num_df` Numerator degrees of freedom for an F-test. `den_df` Denominator degrees of freedom for an F-test. `liberal_lambda` Logical indicator of whether to use the liberal (cohen_f^2\*(num_df+den_df)) or conservative (cohen_f^2\*den_df) calculation of the noncentrality (lambda) parameter estimate. Default is FALSE.

## Value

Returns plots of effect size (x-axis)

## Functions

• `morey_plot.ttest`: Power-sensitivity plot for t-tests

• `morey_plot.ftest`: Power-sensitivity plot for F-tests

## References

Morey, R.D. (2020). Power and precision Why the push for replacing “power” with “precision” is misguided. Retrieved from: https://richarddmorey.medium.com/power-and-precision-47f644ddea5e

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```## Not run: # t-test example ------ # Sensitivity for cohen's d from .1 to .5 # sample sizes of 10 and 20 # alpha levels .05 and .075 # type will be paired and one sided # Set effect sizes with seq function (?seq) morey_plot.ttest(es = seq(.1,.5,.01), n = c(10,20), alpha_level = c(.05,.075), type = "paired", alternative = "one.sided") ## End(Not run) ```

Superpower documentation built on May 25, 2021, 9:07 a.m.