![]() In the above case, what should my numerator df be? I first thought it was 1, because (2-1)(2-1) = 1, but if I want to include the three-way interaction term between the categorical IVs and the continuous IV (covariate in G*Power), then should I add one more df in the power analysis? I have attached the screenshot of it below. Choose which calculation you desire, enter the relevant population values for mu1 (mean of population 1), mu2 (mean of population 2), and sigma (common standard. However, as far as I understand ANCOVA assumes no interaction between co-variates and IVs, whereas, in my case, there will be interactions. I expect one two-way and one three-way interaction between the IVs. I have two categorical IVs (2 x 2), one continuous IV (I put this as a covariate in G*Power), and one continuous DV. Since my main hypothesis revolves around interaction terms, I am using ANCOVA in G*Power analysis to calculate the required sample size. The null hypothesis can be written as the population mean 0. SAS can handle two different types of distributions, namely the normal distribution and the lognormal distribution. This calculator computes the minimum number of necessary samples to meet the desired statistical constraints. One needs to specify the distribution of the population. ![]() I am trying to conduct a power analysis on a hierarchical regression with interaction effects. One sample mean t-test Let’s first take a look at the t-test for one sample means. I wrote a similar post just before, but I realized that I put wrong information there, hence I deleted it, and have re-written here
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