Is there a link that provides the mathematical background?
Thanks in advance.
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Well, it's the basic linear model hypothesis test statistic that each coefficient in the model is significantly different from the null hypothesis that the coefficient is zero. It's simply the value of the coefficient divided by the overall model standard error. That's what the doc says:
tStat—t-statistic for each coefficient to test the null hypothesis that the corresponding coefficient is zero against the alternative that it is different from zero, given the other predictors in the model. Note thattStat = Estimate/SE. For example, thet-statistic for the intercept is 47.977/3.8785 = 12.37.
pValue—p-value for thet-statistic of the hypothesis test that the corresponding coefficient is equal to zero or not. For example, thep-value of thet-statistic forx2is greater than 0.05, so this term is not significant at the 5% significance level given the other terms in the model.
https://dss.princeton.edu/online_help/analysis/interpreting_regression.htm is one set of class notes; it's covered in any text on regression analysis. I'm long in the tooth; my reference was always Draper and Smith, Applied Regression Analysis for introductory text; I'm sure the edition I have is long out of print...
What most people mean by "logistic tregression" is a binomial response: number of "successes" vs. number of "failures". Unless you specifically need to fit a model for a multinomial response (more than just two response categories), I'd suggest you use glmfit.
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