These data arise in several areas of investigation and are characterized by the presence of correlation between observations within the same group.
Some examples are repeated measures data, longitudinal studies, and nested designs.
Classical modeling techniques which assume independence of the observations are not appropriate for grouped data. These models are becoming increasingly popular because of the development of reliable and efficient software for fitting them, which, in recent years, have become available in commercial packages. Ongoing research in mixed-effects models at the Statistics and Data Mining Research Department focuses on computational and methodological aspects, in the main areas listed below. It extends the linear and nonlinear modeling facilities available in release 3 of S and S-PLUS and is available for Unix and Windows platforms. The following research activities are related to the NLME software.