Partially linear models are linear regression models where one component is allowed to vary nonparametrically. Generalized partially linear models generalize this case from linear regression to the quasi-likelihood setting of standard GLIMs, thus encompassing a larger class models including...

Mixed-effects models contain both fixed and random effects. The fixed effects are analogous to standard regression coefficients and are estimated directly. The random effects are not directly estimated but instead are summarized according to their estimated variances and covariances, known as...

Partially linear models are linear regression models where one component is allowed to vary nonparametrically. Generalized partially linear models generalize this case from linear regression to the quasi-likelihood setting of standard GLIMs, thus encompassing a larger class models including...

Stata version 9 includes the new command xtmixed, for fitting linear mixed models. Mixed models contain both fixed and random effects. The fixed effects are analagous to standard regression coefficients and are estimated directly. The random effects are not directly estimated but are summarized...