๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Selection of a Covariance Structure for Growth Curves

โœ Scribed by Elaine M. Keramidas; Jack C. Lee

Publisher
John Wiley and Sons
Year
1995
Tongue
English
Weight
744 KB
Volume
37
Category
Article
ISSN
0323-3847

No coin nor oath required. For personal study only.

๐Ÿ“œ SIMILAR VOLUMES

LR Tests for Random-Coefficient Covarian
LR Tests for Random-Coefficient Covariance Structures in an Extended Growth Curve Model
โœ Yasunori Fujikoshi; Dietrich von Rosen ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 188 KB

This paper is concerned with an extended growth curve model with two withinindividual design matrices which are hierarchically related. For the model some random-coefficient covariance structures are reduced. LR tests for testing the adequacy of each of these random-coefficient structures and their

Bayesian Local Influence for the Growth
Bayesian Local Influence for the Growth Curve Model with Rao's Simple Covariance Structure
โœ Jian-Xin Pan; Kai-Tai Fang; Erkki P. Liski ๐Ÿ“‚ Article ๐Ÿ“… 1996 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 916 KB

In this paper, the Bayesian local influence approach is employed to diagnose the adequacy of the growth curve model with Rao's simple covariance structure, based on the Kullback Leibler divergence. The Bayesian Hessian matrices of the model are investigated in detail under an abstract perturbation s

Variable Selection for the Growth Curve
Variable Selection for the Growth Curve Model
โœ Kenichi Satoh; Mika Kobayashi; Yasunori Fujikoshi ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 914 KB

In this paper we consider the problem of selecting the covariables within individuals in the growth curve model. We propose two modifications of AIC and MIC (Cp-static), which have improvements on the bias properties. Asymptotic distributions of variable slection criteria are derived under a general