The measure is in the same spirit as Achen's (1982) "level importance" measure for linear models and thus fills an important gap in logit regression analysis. We show, on the basis of simulations and ...

After fitting survival data with a linear regression model, it is important to know how to use the results to make prediction of the t-year survival probability or median failure time for future ...

You construct a generalized linear model by deciding on response and explanatory variables for your data and choosing an appropriate link function and response probability distribution. Some examples ...