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...t sure how to resolve the issues. glm.fit: algorithm did not converge glm.fit: fitted probabilities numerically 0 or 1 occurred d1 = data.frame(mwin=c(mwin), mbid=c(mbid)) m1 = zelig(mwin ~ mbid, data=d1, model="logit") summary(m1) plot(mwin ~ mbid) > str(d1)'data.frame': 66514 obs. of 2 variables: $ mwin: Factor w/ 3 levels "","ACCEPTED",..: 2 2 2 2 2 2 2 2 2 2 ... $ mbid: int 700 300 700 300 500 300 300 700 300 300 ... Can anyone tell me what I should do to fix the warnings. -- *Abraham Mathew Statistical Analyst www.amathew.com 720-648-010...

...39;s the expected probability of winning. and so forth. I ran the following code, but I'm getting some weird results. d1 = data.frame(mwin=c(mwin), mbid=c(mbid)) str(d1) m1 = zelig(mwin ~ mbid, data=d1, model="logit") summary(m1) plot(mwin ~ mbid) > str(d1)'data.frame': 66514 obs. of 2 variables: $ mwin: int 2 2 2 2 2 2 2 2 2 2 ... $ mbid: int 700 300 700 300 500 300 300 700 300 300 ... library(Zelig) x.out <- setx(m1, mbid=300) s.out <- sim(m1, x = x.out) summary(s.out) plot(s.out) When I run with mbid as 300, I get 49%. At 500, it's 49% and at 700...