R2_prec

Compute Precision Analyses for R-Squared
This approach simply loops a function from MBESS

Statistical power analysis for designs including t-tests, correlations,
multiple regression, ANOVA, mediation, and logistic regression. Functions accompany
Aberson (2019) <doi:10.4324/9781315171500>.

Chris Aberson

pwr2ppl

Power Analyses for Common Designs (Power to the People)

R2_prec function

<dl><dt>R2</dt>
<dd>R-squared</dd>
<dt>nlow</dt>
<dd>starting sample size</dd>
<dt>nhigh</dt>
<dd>ending sample size</dd>
<dt>pred</dt>
<dd>Number of Predictors</dd>
<dt>ci</dt>
<dd>Type of Confidence Interval (e.g., .95)</dd>
<dt>by</dt>
<dd>Incremental increase in sample (e.g. nlow = 10, nhigh = 24, by = 2, produces estimates of 10, 12, and 14)</dd></dl>

Arguments

Compute Precision Analyses for R-Squared
This approach simply loops a function from MBESS — R2_prec

<dl>

<dt>R2</dt>
<dd>R-squared</dd>


<dt>nlow</dt>
<dd>starting sample size</dd>


<dt>nhigh</dt>
<dd>ending sample size</dd>


<dt>pred</dt>
<dd>Number of Predictors</dd>


<dt>ci</dt>
<dd>Type of Confidence Interval (e.g., .95)</dd>


<dt>by</dt>
<dd>Incremental increase in sample (e.g. nlow = 10, nhigh = 24, by = 2, produces estimates of 10, 12, and 14)</dd>

</dl>

R2_prec: Compute Precision Analyses for R-Squared This approach simply loops a function from MBESS

Description

Usage

Value

Arguments

Examples