AIC and combined discrete/continuous models
Explains why AIC comparisons between discrete and continuous statistical models are invalid, using examples with binomial and Normal distributions.
Explains why AIC comparisons between discrete and continuous statistical models are invalid, using examples with binomial and Normal distributions.
Comparison of statistical tests (Wald, score, likelihood ratio, Rao-Scott) for generalized linear models in survey data, analyzing Type I error and power.
A statistical analysis of variance estimation for generalized linear models with crossed clustering, using old R code and sandwich estimators.
The author discusses the unexpected computational challenges of implementing score tests for generalized linear models in survey statistics.
Explains the relationship between Wald, score, and likelihood ratio tests in statistical modeling using visual diagrams and R code examples.
A method for faster generalized linear models on large datasets using a single database query and one Newton-Raphson iteration.