Hi Team, I am creating *my first* Logistic regression on R Studio. I am working on a C-SAT data where rating (score) 0-8 is a dis-sat whereas 9-10 are SAT. As these were in numeric form so i had as below created 2 classes:
new$survey[new$score>=0 & new$score<=8]<- 0 new$survey[new$score>=9]<- 1 This works fine however the class still shows as "numeric" and levels shows as "NULL". Do i still need to use "as.factor" to let R know these are categorical variables. Also i have used the below code to run a logistic regression with all the possible predictor variables: glm.fit= glm(survey ~ support_cat + region+ support_lvl+ skill_group+ application_area+ functional_area+ repS+ case_age+ case_status+ severity_level+ sla_status+ delivery_segmentation, data = SFDC, family = binomial) But it throws an error:- Warning messages: 1: glm.fit: algorithm did not converge 2: glm.fit: fitted probabilities numerically 0 or 1 occurred I checked online for the error and it says: "glm() uses an iterative re-weighted least squares algorithm. The algorithm hit the maximum number of allowed iterations before signalling convergence. The default, documented in ?glm.control is 25." Kindly suggest on the above case and if i have to change my outcome var as as.factor. Thank you, Shivi [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.