Akaike Information Criterion (AIC) and the c-statistic (area under ROC curve) are two measures of model fit for logistic regression. I am having trouble explaining what is going on when the results of ...
Generalized Linear Model in SPSS with common values among predictors treated as subpopulations. Why?
I am teaching a class on logistic regression with SPSS. The textbook supplies a sample data set with a binary predictor and two numeric covariates. The sample contains 1000 rows and a number of these ...
I am ranking candidate models using Akaike information criterion (AIC). All my models have positive -2*LL (log likelihood) values which as far as I understand is expected under certain circumstances ...
I run a backward variable selection logistic regression and find out the SAS program selected 12 variables and give me the output like this: It is funny that my configuration of the SAS ...
I am running a logistic model. The actual model dataset has more than 100 variables but I am choosing a test data set in which there are around 25 variables. Before that I also made a dataset which ...
In answering this question John Christie suggested that the fit of logistic regression models should be assessed by evaluating the residuals. I'm familiar with how to interpret residuals in OLS, they ...