AbstractThis paper is concerned with an extended growth curve model with two within-individual 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 asymptotic null distributions are derived
This paper examines the correlated random coecient model. It extends the analysis of Swamy (1971, 19...
AbstractA crucial step in designing a new study is to estimate the required sample size. For a desig...
Published: 17 April 2018Latent Growth Curve Models (LGCM) have become a standard technique to model ...
AbstractThis paper considers three types of problems: (i) the problem of independence of two sets, (...
AbstractIn the present paper, we consider the likelihood ratio criterion (LRC) for mean structure in...
Random coefficient linear regression models have been employed in economics, medical and psychologic...
In this dissertation we consider the growth curve or generalized MANOVA model in its most general fo...
Hierarchical growth models are widely used in longitudinal studies to investigate individual changes...
In this paper we consider the problem of testing (a) sphericity and (b) intraclass covariance struct...
Using a Monte Carlo simulation and the Kenward-Roger (KR) correction for degrees of freedom this pap...
Growth curve analysis is useful in studies with repeated measurements on experimental units. They en...
AbstractIn this paper, we propose a framework of outer product least squares for covariance (COPLS) ...
In this article, we consider the problem of testing (a) sphericity and (b) intraclass covariance str...
AbstractThe null hypothesis that the error vectors in a multivariate linear model are independent is...
In this paper, we propose nonparametric locally and asymptotically optimal tests for the problem of ...
This paper examines the correlated random coecient model. It extends the analysis of Swamy (1971, 19...
AbstractA crucial step in designing a new study is to estimate the required sample size. For a desig...
Published: 17 April 2018Latent Growth Curve Models (LGCM) have become a standard technique to model ...
AbstractThis paper considers three types of problems: (i) the problem of independence of two sets, (...
AbstractIn the present paper, we consider the likelihood ratio criterion (LRC) for mean structure in...
Random coefficient linear regression models have been employed in economics, medical and psychologic...
In this dissertation we consider the growth curve or generalized MANOVA model in its most general fo...
Hierarchical growth models are widely used in longitudinal studies to investigate individual changes...
In this paper we consider the problem of testing (a) sphericity and (b) intraclass covariance struct...
Using a Monte Carlo simulation and the Kenward-Roger (KR) correction for degrees of freedom this pap...
Growth curve analysis is useful in studies with repeated measurements on experimental units. They en...
AbstractIn this paper, we propose a framework of outer product least squares for covariance (COPLS) ...
In this article, we consider the problem of testing (a) sphericity and (b) intraclass covariance str...
AbstractThe null hypothesis that the error vectors in a multivariate linear model are independent is...
In this paper, we propose nonparametric locally and asymptotically optimal tests for the problem of ...
This paper examines the correlated random coecient model. It extends the analysis of Swamy (1971, 19...
AbstractA crucial step in designing a new study is to estimate the required sample size. For a desig...
Published: 17 April 2018Latent Growth Curve Models (LGCM) have become a standard technique to model ...