- Thread starter DavidB
- Start date

I wouldn't dichotomize scores, since you will lose information. Also, I did not completely follow your above description, but you can't have an outcome with odds ratios and R^2. You can get R^2 out of a logistic regression, but they are considered useless.

The easiest was to do this would be simulations of pre data with a change added to those values, then conduct your test statistic and repeat this process and repeat this process for multiple sample sizes.

I wouldn't dichotomize scores, since you will lose information. Also, I did not completely follow your above description, but you can't have an outcome with odds ratios and R^2. You can get R^2 out of a logistic regression, but they are considered useless.

The easiest was to do this would be simulations of pre data with a change added to those values, then conduct your test statistic and repeat this process and repeat this process for multiple sample sizes.

--> So if I do logistic regression, I'm a little confused about how to set up the power analysis. (The R^2 from G*Power referred to the x variable parameter, not the outcome.) I don't know what my main predictor is, because the data are paired. The predictor isn't receiving the drug, because everyone receives it. Should I be using a different test all together? And if so, can it eventually incorporate other confounders? The one-tailed one-sample binomial test would work initially, but doesn't allow for incorporating confounders.