Link functions
Identity
Log
Logit
Probit
Complementary log-log
Power
Odds power
Negative binomial
Log-log
Log-complement
Families
Gaussian (normal)
Inverse Gaussian
Bernoulli/binomial
Poisson
Negative binomial
Gamma
Choice of estimation method
Maximum likelihood
Iteratively reweighted least squares (IRLS)
Customizable functions
User-defined link functions
User-defined variance functions
User-defined HAC kernels
Choice of variance estimates and standard errors
Inverse Hessian
Outer product of the gradients (OPG)
Observed information matrix
Expected information matrix
Robust Huber/White/sandwich estimator
Robust variance with clustered/correlated data
Heteroskedasticity- and autocorrelation-consistent (HAC) with Newey–West, Gallant, Anderson, or user-written kernel
Jackknife
Bootstrap
GEE estimation for panel data
Correlation structures
Exchangeable
Independent
Unstructured
Autoregressive
Stationary
Nonstationary
Fixed
Conventional, robust, bootstrap, and jackknife standard errors
Multilevel mixed-effects GLMs*
Two-, three-, and higher-level models
Nested (hierarchical) and crossed models
Random intercepts and slopes
Bayesian estimation
Postestimation Selector*
View and run all postestimation features for your command
Automatically updated as estimation commands are run
Watch Postestimation Selector.
Predicts
Expected value of dependent variable
Anscombe residual
Cook’s distance
Deviance residual
Diagonal of hat matrix
Likelihood residual
Pearson residual
Response residual
Score residual
Working residual
Factor variables
Automatically create indicators based on categorical variables
Form interactions among discrete and continuous variables
Include polynomial terms
Perform contrasts of categories/levels
Marginal analysis
Estimated marginal means
Marginal and partial effects
Average marginal and partial effects
Least-squares means
Predictive margins
Adjusted predictions, means, and effects
Works with multiple outcomes simultaneously
Contrasts of margins
Pairwise comparisons of margins
Profile plots
Graphs of margins and marginal effects
A single continuous variable
Interactions of categorical variables
Interactions of categorical and continuous variables
Interactions of two continuous variables
Additional resource
Generalized Linear Models and Extensions, Third Edition
