Add to ORKGWe outline Optimal Statistical techniques for the analysis of change in longitudinal studies. The particular interest of Structural Modeling Equations, compared with general Multivariate Analysis of Variance ManoVa model
This thesis develops some statistical models for the multivariate analysis of longitudinal data on ...
The Generalized Estimating Equations (GEE) method is one of the most commonly used statistical metho...
UnrestrictedIn 1988, McArdle identified issues modeling multivariate growth using what he termed “se...
This paper is a review of statistical techniques for studying longitudinal data. In particular, we o...
In this paper we review different structural equation models for the analysis of longitudinal data:...
Longitudinal research designs concetrate on the questions of stability and change of the characteris...
Longitudinal experiments often involve multiple outcomes measured repeatedly within a set of study p...
In the health and social sciences, longitudinal data have often been analyzed without taking into ac...
Longitudinal data sets consist of repeated observations of an outcome over time, and a corresponding...
Although many books currently available describe statistical models and methods for analyzing longit...
A modeling paradigm is proposed for covariate, variance and working correlation structure selection ...
Within the past few decades, methodologists have made major advances in statistical methods for the ...
Traditional approach to analysis of change (MANOVA) was based on assumption that change consists of ...
We provide an expository presentation f multivariate analysis of variance (MANOVA) for both consumer...
Canonical variate analysis (CVA) is a widely used method for analyzing group structure in multivaria...
This thesis develops some statistical models for the multivariate analysis of longitudinal data on ...
The Generalized Estimating Equations (GEE) method is one of the most commonly used statistical metho...
UnrestrictedIn 1988, McArdle identified issues modeling multivariate growth using what he termed “se...
This paper is a review of statistical techniques for studying longitudinal data. In particular, we o...
In this paper we review different structural equation models for the analysis of longitudinal data:...
Longitudinal research designs concetrate on the questions of stability and change of the characteris...
Longitudinal experiments often involve multiple outcomes measured repeatedly within a set of study p...
In the health and social sciences, longitudinal data have often been analyzed without taking into ac...
Longitudinal data sets consist of repeated observations of an outcome over time, and a corresponding...
Although many books currently available describe statistical models and methods for analyzing longit...
A modeling paradigm is proposed for covariate, variance and working correlation structure selection ...
Within the past few decades, methodologists have made major advances in statistical methods for the ...
Traditional approach to analysis of change (MANOVA) was based on assumption that change consists of ...
We provide an expository presentation f multivariate analysis of variance (MANOVA) for both consumer...
Canonical variate analysis (CVA) is a widely used method for analyzing group structure in multivaria...
This thesis develops some statistical models for the multivariate analysis of longitudinal data on ...
The Generalized Estimating Equations (GEE) method is one of the most commonly used statistical metho...
UnrestrictedIn 1988, McArdle identified issues modeling multivariate growth using what he termed “se...