Stata’s xtmixed command can be used to fit mixed models, models that contain both fixed and random effects. The fixed effects are merely the coefficients from a standard linear regression. The random effects are not directly estimated but summarized by their variance components, which are estimated from the data. As such, xtmixed is typically used to incorporate complex and multilevel random-effects structures into standard linear regression. xtmixed’s syntax is complex but versatile, allowing it to be used widely, even for situations that do not fit the classical "mixed" framework. In this talk, I will give a tutorial on uses of xtmixed not commonly considered, including examples of heteroskedastic errors, group structures on random effects, and smoothing via penalized splines.
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