I have a population in which my dependent variable is binary with a highly-skewed distribution: Very few records are 1 (doers), most records are 0 (non-doers). I'm using logistic regression to predict the value of this variable.
To deal with this rare-event situation, I made multiple samples of non-doers that are size-matched to the number of doers (e.g., sample 1 has the 100 doers and 100 non-doers, sample 2 has the 100 doers and a different set of 100 non-doers, etc.).
I fit a logistic regression to each of these samples and computed t-values to quantify the degree to which the independent variable coefficients are reliably different from 0. That is, each independent variable is associated with1 t-value per sample.
Can I compute statistics of t-values? Can I compute the average, standard error, and standard deviation of these t-values? I don't think I can do it for p-values and I know that correlation coefficients need to be transformed to z-values first, but I don't know what's acceptable for t-values.