Also is linear regression acceptable to bayesians since no normality required.++My understanding is that logit first fits a linear regression on the dichotomous Y and then forces this to lie between 0 and 1 via the logit y=1(1+e^x), finally the log likelihood is calculated as the P(estimate|D) - was this P(estimate|d), I forget the commonly cited log-likelihood for logit but was it calculated via bayes theorem?++Sorry about newbie question..
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