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
LR test for random-effects covariance structure in a parallel profile model
โ Scribed by Takahisa Yokoyama
- Publisher
- Springer Japan
- Year
- 1995
- Tongue
- English
- Weight
- 477 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0020-3157
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๐ SIMILAR VOLUMES
Let \(\boldsymbol{W}\) be a \(p \times p\) matrix distributed according to the Wishart distribution \(W_{p}(n, \boldsymbol{\Phi})\) with \(\boldsymbol{\Phi}\) positive definite and \(n \geqslant p\). Let \(\left(m / \sigma^{2}\right) g\) be distributed according to the chi-squared distribution \(\ch
In this paper we propose test statistics for a general hypothesis concerning the adequacy of multivariate random-effects covariance structures in a multivariate growth curve model with differing numbers of random effects (Lange, N., N.M. Laird, J. Amer. Statist. Assoc. 84 (198!)1 241 247). Since the
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