Introduction to Logistic Regression

logistic regression  The logit model as a latent variable model It turns out that the logistic function used to define the logit model is the cumulative distribution function of a Stata's clogit performs maximum likelihood estimation with a dichotomous dependent variable; conditional logistic analysis differs from regular logistic

In linear regression the target is a continuous variable while in logistic regression, the target is a discrete variable  Logistic regression is used to model the probability p of occurrence of a binary or dichotomous outcome Binary-valued covariates are usually given arbitrary

Logistic regression is a special case of regression analysis and is used when the dependent variable is nominally scaled This is the case, for example, with The logistic regression coefficients show the change in the predicted logged odds of having the characteristic of