Chi sq = inf (Firth's logistic regression) [closed]

I want coefficients for ‘Isolate’, ‘Temperature’ and ‘Isolate*Temperature’. I want to use these coefficients to plot probabilities of death (for each isolate) as a function of temperature (25-50C). What would be the best way to analyze this data? I've read that Firth's logistic regression is probably best but if the model has "blown up" then I'm not sure how to proceed. Any thoughts would be greatly appreciated. Thanks.

Here is my output from firth's logistic regression analysis:

Can anyone explain why the chi square values are equal to infinity for the intercept and temp?

closed as unclear what you're asking by Xi'an, Andy, gung♦, kjetil b halvorsen, Nick CoxJan 11 '15 at 10:33

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• Both Isolate and Temp are numeric variables? Maybe scaling them (ie, by their standard deviation, or by 100) would help? – Andrew M Jan 11 '15 at 7:18
• Suggesting this be reopened because Firths method is still susceptible the the ordinary or typical pitfalls in logistic regression. So those should be avaialble to explain such results. A logistic regression coefficient of 22 is not entirely meaningless, but it is certainly "informative" ... informative of a problem. – DWin Jul 30 at 1:34