Abstract
Multilevel data structures, such as data with individuals within groups, groups within areas, etc., arise in a variety of contexts. Regression models for such data allow for variation of the within‐group regression coefficients. Since some of the explanatory variables may be observed subject to measurement error, it is desirable to define models that combine within‐group correlation and measurement error. We discuss a general model formulation and a scoring algorithm for maximum likelihood estimation.

This publication has 0 references indexed in Scilit: