Linear equality constraints in the general linear mixed model

被引:15
作者
Edwards, LJ [1 ]
Stewart, PW [1 ]
Muller, KE [1 ]
Helms, RW [1 ]
机构
[1] Univ N Carolina, Sch Publ Hlth, Dept Biostat, Chapel Hill, NC 27599 USA
关键词
cognitive development; correlated outcomes; IQ; longitudinal data analysis; parameter constraints; random effect models; singular-value decomposition; transformations;
D O I
10.1111/j.0006-341X.2001.01185.x
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Scientists may wish to analyze correlated outcome data with constraints among the responses. For example, piecewise linear regression in a longitudinal data analysis can require use of a general linear mixed model combined with linear parameter constraints. Although well developed for standard univariate models, there are no general results that allow a data analyst to specify a mixed model equation in conjunction with a set of constraints on the parameters. We resolve the difficulty by precisely describing conditions that allow specifying linear parameter constraints that insure the validity of estimates and tests in a general linear mixed model. The recommended approach requires only straightforward and noniterative calculations to implement. We illustrate the convenience and advantages of the methods with a comparison of cognitive developmental patterns in a study of individuals from infancy to early adulthood for children from low-income families.
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页码:1185 / 1190
页数:6
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