# Multiple Regression: 4 predictors

Large Effect Size

Power analysis for a multiple regression with four predictors was conducted in G*Power to determine a sufficient sample size using an alpha of 0.05, a power of 0.80, and a large effect size (f2 = 0.35) (Faul et al., 2013). Based on the aforementioned assumptions, the desired sample size is 40.

Medium Effect Size

Power analysis for a multiple regression with four predictors was conducted in G*Power to determine a sufficient sample size using an alpha of 0.05, a power of 0.80, and a medium effect size (f2 = 0.15) (Faul et al., 2013). Based on the aforementioned assumptions, the desired sample size is 85.

Small Effect Size

Power analysis for a multiple regression with four predictors was conducted in G*Power to determine a sufficient sample size using an alpha of 0.05, a power of 0.80, and a small effect size (f2 = 0.02) (Faul et al., 2013). Based on the aforementioned assumptions, the desired sample size is 602.

References

Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2013). G*Power Version 3.1.7 [computer software]. Uiversität Kiel, Germany. Retrieved from http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3/download-and-register

Statistics Solutions. (2013). Sample Size Write-up [WWW Document]. Retrieved from http://www.statisticssolutions.com/resources/sample-size-calculator/multiple-regression-predictors/multiple-regression-4-predictors/