multiple regression 6 predictors

Statistics Solutions Advancement Through Clarity http://www.statisticssolutions.com Multiple Regression: 6 predictors L...

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Statistics Solutions Advancement Through Clarity http://www.statisticssolutions.com

Multiple Regression: 6 predictors Large Effect Size Power analysis for a multiple regression with six 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 46. Medium Effect Size Power analysis for a multiple regression with six 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 98. Small Effect Size Power analysis for a multiple regression with six 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 688. 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.uniduesseldorf.de/abteilungen/aap/gpower3/download-and-register Statistics Solutions. (2013). Sample Size Write-up [WWW Document]. Retrieved from http://www.st atisticssolutions.com/resources/sample-size-calculator/multiple-regression-predictors/multipleregression-6-predictors/

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