[R] logistic regression - glm.fit: fitted probabilities numerically 0 or 1 occurred
pdalgd at gmail.com
Thu Dec 1 19:55:18 CET 2011
On Dec 1, 2011, at 18:54 , Ben quant wrote:
> Sorry if this is a duplicate: This is a re-post because the pdf's mentioned
> below did not go through.
Still not there. Sometimes it's because your mailer doesn't label them with the appropriate mime-type (e.g. as application/octet-stream, which is "arbitrary binary"). Anyways, see below
> With the above data I do:
>> l_logit = glm(y~x, data=as.data.frame(l_yx),
> Warning message:
> glm.fit: fitted probabilities numerically 0 or 1 occurred
> Why am I getting this warning when I have data points of varying values for
> y=1 and y=0? In other words, I don't think I have the linear separation
> issue discussed in one of the links I provided.
I bet that you do... You can get the warning without that effect (one of my own examples is the probability of menarche in a data set that includes infants and old age pensioners), but not with a huge odds ratio as well. Take a look at
d <- as.data.frame(l_yx)
if it comes out as all zeros followed by all ones or vice versa, then you have the problem.
> PS - Then I do this and I get a odds ratio a crazy size:
>> l_sm = summary(l_logit) # coef pval is $coefficients, log odds
>> l_exp_coef = exp(l_logit$coefficients) # exponentiate the
> So for one unit increase in the predictor variable I get 3160.781%
> (3161.781 - 1 = 3160.781) increase in odds? That can't be correct either.
> How do I correct for this issue? (I tried multiplying the predictor
> variables by a constant and the odds ratio goes down, but the warning above
> still persists and shouldn't the odds ratio be predictor variable size
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
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