# alpha_standardized: Compute standardized alpha level based on unstandardized... In Superpower: Simulation-Based Power Analysis for Factorial Designs

## Description

Compute standardized alpha level based on unstandardized alpha level and the number of observations N.

## Usage

 `1` ```alpha_standardized(alpha, N, standardize_N = 100) ```

## Arguments

 `alpha` The unstandardized alpha level (e.g., 0.05), independent of the sample size. `N` The number of observations (e.g., the sample size) in the dataset `standardize_N` The nuber of observations (e.g., the sample size) you want to use to standardize the alpha level for. Defaults to 100 (base on Good, 1982).

## References

Good, I. J. (1982). C140. Standardized tail-area probabilities. Journal of Statistical Computation and Simulation, 16(1), 65–66. <https://doi.org/10.1080/00949658208810607>

## Examples

 ```1 2 3 4 5 6 7 8``` ```## Check it yields .05 for N = 100: alpha_standardized(alpha = 0.05, N = 100) ## Check it yields .05 for N = 200: alpha_standardized(alpha = 0.07071068, N = 200) ## Which alpha should we use with N = 200? alpha_standardized(alpha = 0.05, N = 200) ## You can change the standardization N, repeating the example above: alpha_standardized(alpha = 0.05, N = 100, standardize_N = 200) ```

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