DF When calculating Chi Square Sample Size I was wondering if someone could provide me some insights on sample size calculation for Chi Square tests.
$$\begin{array}{c|c|c|} 
 & \text{Group 1} & \text{Group 2}& \text{χ2} \\ \
\text{var 1} & a  & b& p=  \\ \hline
\text{var 2} & c  & d& p= \\ \hline
\text{var 3} & e  & f& p= \\ \hline
\end{array}$$
I have a table like this where I am doing simple chi square test for each variable. So there are 3 tests. When calculating sample size using G power is my Df=1? Since Df=(c-1)(r-1) for each individual test.
Moreover, the sample size I get is for one variable I assume. How do I adjust for multiple variables?
Thank You for any help
 A: Amending my comment: The df will be 1 since it amounts to a test of two proportions. If you are willing to assume that tests for var1–var3 are independant, a very simple yet conservative procedure would be to use Bonferroni correction.
I don't think power analysis is required (1) in the case of a retrospective study and (2) when the variables in question are probably not the main outcome.

*

*Contrary to a prospective study, using information from the sample data, rather than expected effect size--fixed a priori, in a retrospective study is controversial. Post-hoc power analysis has been discussed at length on this site, but see, e.g., Thomas, L. (1997). Retrospective Power Analysis, Conservation Biology, 11(1), 276–280.


*Secondary endpoints are usually treated separately. Anyway, the following two references discuss the case of multiple tests in relation to power analysis: Bang, H., S.-H. Jung, and S. George (2005). Sample size calculation for simulation-based multiple-testing procedures. Journal of Biopharmaceutical Statistics, 15, 957–967; Senn, S. and F. Bretz (2007). Power and sample size when multiple endpoints are considered. Pharmaceutical Statistics, 6, 161–170. Note, however, that in both cases those papers focus on randomized clinical trials with multiple endpoints or correlated outcomes.
