Binary Logistic Regression Power Calculator. I When performing the logistic regression test. Power is computed using an approximation which depends on the type of variable.
For logistic regression of a binary dependent variable using several continuous normally distributed independent variables at 80 power at a 005 significance level to detect a change in Prob Y 1 from the value of 0050 at the mean of X to 0100 when X is increased to one standard deviation above the mean requires a sample size of 150. Sample Size and Estimation Problems with Logistic Regression. This calculator will tell you the minimum required sample size for a multiple regression study given the desired probability level the number of predictors in the model the anticipated effect size and the desired statistical power level.
So the dependent variable is binary in nature and I decided to use logistic regression.
Calculating power for simple logistic regression with binary. Such as Poisson regression and polychotomous logistic regression. I have seven independent variables three continuous and four nominal. The procedure fits the usual logistic regression model for binary data in addition to models that have the cumulative link function for ordinal data such as the proportional odds model and the generalized logit model for nominal data.
