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I have a sequence of observed outcomes from independent but not identically distributed Bernoulli trials, and some covariate data. I perform logistic regression, and use it to estimate the probability of each trial succeeding. If I sum these estimates up, do they always add up to the total number of observed successes?

I know that in the absence of covariate data, the MLE of the constant term is the number of successes divided by the number of trials.

Alex
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    i mean, summing estimated probabilities for all observations, i.e. successes and failures. – Alex Sep 02 '16 at 07:06

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Yes, assuming there is an intercept in the model, then the fitted probabilities sum to the number of ones in the sample. This can be seen from the likelihood equations.

kjetil b halvorsen
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