Dear users, In my psychometric test i have applied logistic regression on my data. My data consists of 50 predictors (22 continuous and 28 categorical) plus a binary response.
Using glm(), stepAIC() i didn't get satisfactory result as misclassification rate is too high. I think categorical variables are responsible for this debacle. Some of them have more than 6 level (one has 10 level). Please suggest some better regression model for this situation. If possible you can suggest some article. thanking you. Tirtha -- View this message in context: http://www.nabble.com/Appropriate-regression-model-for-categorical-variables-tf3908982.html#a11083540 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
