I have a logistic regression model and output an $R^2$ value. I then go and add another predictor variable to fit a second model. I can output a new $R^2$ value associated with the second model. When I run an ANOVA test, I see no significant improvement in the second model, but I want to assess the power associated with including the additional variable in model 2.

I have found [an example](http://www.ats.ucla.edu/stat/gpower/multreg.htm) for linear regression that uses an $F$-Test. **I want to do something similar for a logistic regression using G\*Power.** 

But there appears to be very little documentation on multiple logistic regression models like my situation. [I don't know how to do a more detailed power analysis for multiple logistic regression](http://www.biostathandbook.com/multiplelogistic.html).

From what I understand, in G\*Power I set `Test Family == z tests` and `statistical test == logisitic regression`. But I am not sure what to set `R² other X` equal to. Is that the improvement in $R^2$?

Reading the tutorial in **27.4** from the [software manual](http://www.gpower.hhu.de/fileadmin/redaktion/Fakultaeten/Mathematisch-Naturwissenschaftliche_Fakultaet/Psychologie/AAP/gpower/GPowerManual.pdf) makes no variation of $R^2$, whereas [this example](http://www.gpower.hhu.de/fileadmin/redaktion/Fakultaeten/Mathematisch-Naturwissenschaftliche_Fakultaet/Psychologie/AAP/gpower/GPower31-BRM-Paper.pdf), does not discuss the improvements made from $R^2$.