SUGI 28: Smoothing with SAS(r) PROC MIXED

Mixed models are an extension of regression models that allows for incorporation of random effects. The application of mixed-effects models to practical data analysis has greatly expanded with consequent development of theory and computer software. It also turns out that mixed models are closely related to smoothing. Nonparametric regression models, especially the general smoothing spline models, are well known for their ability to fit an arbitrary mean response function. This paper describes the use of the MIXED procedure for fitting nonparametric or semi-parametric regression models. Compared with such SAS procedures as PROC LOESS and PROC TPSPLINE, the use of the PROC MIXED allows the fitting of a wide spectrum of complex non-parametric and semiparametric regression models with simultaneous modeling of trends and covariance structure.