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Is the only reason why fitted probabilities of 0 or 1 occur is that some of your predicting variables(x) are perfect linear combinations of the target(y) variable? Is there any other reason?

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closed as unclear what you're asking by Michael Chernick, AdamO, kjetil b halvorsen, Stephan Kolassa, mdewey Jan 23 '18 at 12:10

Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

  • $\begingroup$ The original question was closed as unclear but I don't think the most recent edit has helped clarify things - "why fitted probabilities occur" should probably say "why fitted probabilities of 0 or 1 occur"? $\endgroup$ – Silverfish Jan 26 '18 at 10:33
  • $\begingroup$ I have updated the question. Thank you @Silverfish! $\endgroup$ – italo Jan 26 '18 at 14:32
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For the reasons, in addition to the situation that the predictor x is a perfect linear combination of the response y, quasi-complete separation will also induce the same error.

Theoretically, this occurs when the maximum likelihood estimate of your regression coefficient does not exist. Simply put, for example, imagine we have an 2*2 contingency table formed by the "problematic" predictor x and the response y, it is possible that there is an 0 in the table, which obstructs the calculation of MLE. This situation (quasi-complete separation) induce the "fitted probabilities numerically 0 or 1 occurred" error. Hope it helps.

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    $\begingroup$ You're welcome. Btw, if you are confused about the solution about this problem, you could also consult this post and a nicely formatted solution is written by @Scortchi. stats.stackexchange.com/questions/11109/… $\endgroup$ – son520804 Jan 23 '18 at 1:13

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