Hi, very likely your data exhibit quasi-separation which cause (log)Lik to be monotone and thus ML estimate do not exist. However you can rely on point estimate and use LRT to test for its significance. Or Better: have a look to brlr or logistf packages which bypass the monotone-likelihood problem by using penalized likelihood.
Best, vito Taka Matzmoto wrote: > Hello R users > > I ran more than 100 logistic regression analyses. Some of the analyses gave > me this kind warning below. > > ########################################################### > Warning messages: > 1: algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, > start = start, etastart = etastart, ... > 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = > Y, weights = weights, start = start, etastart = etastart, ... > ########################################################### > > For those cases for which I got the warning messages, shouldn't I rely on > coefficents ? It looks like I can still extract coefficients from R outputs > > Are there any ways to avoid these warning messages ? or are these due to the > problems with my data (e.g., perfect separation) > > Any help or advice would be appreciated > > Thank you > > TM > > ______________________________________________ > 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 > -- ==================================== Vito M.R. Muggeo Dip.to Sc Statist e Matem `Vianelli' Università di Palermo viale delle Scienze, edificio 13 90128 Palermo - ITALY tel: 091 6626240 fax: 091 485726/485612 ______________________________________________ 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
