Add to ORKGLatent growth models have been widely applied to univariate longitudinal data. In this work we extend these models to deal with multidimensional continuous measures by combining the classical factor analysis and the latent curve approach. A full maximum likelihood estimation is used to get parameter estimates
Curran and Bollen combined two models for longitudinal panel data: the latent growth curve model and...
none3noneBianconcini S.; Cagnone S.; Monari P.Bianconcini S.; Cagnone S.; Monari P
Intensive longitudinal studies are becoming progressively more prevalent across many social science ...
Latent growth models have been widely applied to univariate longitudinal data. In this work we exten...
We propose a latent variable approach for modeling repeated multiple continuous responses. First the...
UnrestrictedIn 1988, McArdle identified issues modeling multivariate growth using what he termed “se...
This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for a...
Multiple outcomes are often used to properly characterize an effect of interest. This paper proposes...
The paper proposes a full information maximum likelihood estimation method for modelling multivariat...
Repeated measures and repeated events data have a hierarchical structure which can be analysed using...
Longitudinal measurements of human growth present special difficulties for statistical analysis, bot...
latent variable model for the analysis of multivariate mixed longitudinal data is proposed. It exten...
Latent growth models are often used to measure individual trajectories representing change over time...
<p>Latent Growth Curve Model: Parameter Estimates for Intercepts, Slopes and Correlations of Slopes ...
A general latent normal model for multilevel data with mixtures of response types is extended in the...
Curran and Bollen combined two models for longitudinal panel data: the latent growth curve model and...
none3noneBianconcini S.; Cagnone S.; Monari P.Bianconcini S.; Cagnone S.; Monari P
Intensive longitudinal studies are becoming progressively more prevalent across many social science ...
Latent growth models have been widely applied to univariate longitudinal data. In this work we exten...
We propose a latent variable approach for modeling repeated multiple continuous responses. First the...
UnrestrictedIn 1988, McArdle identified issues modeling multivariate growth using what he termed “se...
This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for a...
Multiple outcomes are often used to properly characterize an effect of interest. This paper proposes...
The paper proposes a full information maximum likelihood estimation method for modelling multivariat...
Repeated measures and repeated events data have a hierarchical structure which can be analysed using...
Longitudinal measurements of human growth present special difficulties for statistical analysis, bot...
latent variable model for the analysis of multivariate mixed longitudinal data is proposed. It exten...
Latent growth models are often used to measure individual trajectories representing change over time...
<p>Latent Growth Curve Model: Parameter Estimates for Intercepts, Slopes and Correlations of Slopes ...
A general latent normal model for multilevel data with mixtures of response types is extended in the...
Curran and Bollen combined two models for longitudinal panel data: the latent growth curve model and...
none3noneBianconcini S.; Cagnone S.; Monari P.Bianconcini S.; Cagnone S.; Monari P
Intensive longitudinal studies are becoming progressively more prevalent across many social science ...