Latent variable models are commonly used in medical statistics, although often not referred to under this name. In this paper we describe classical latent variable models such as factor analysis, item response theory, latent class models and structural equation models. Their usefulness in medical research is demon-strated using real data. Examples include measurement of forced expiratory flow, measurement of physical disability, diagnosis of myocardial infarction and modelling the determinants of clients ’ satisfaction with counsellors ’ interviews.
Many applications of biomedical science involve unobservable constructs, from measurement of health ...
Although statistical models serve as the foundation of data analysis in clinical studies, their inte...
Abstract Background Structural equation modeling (SEM) is a set of statistical techniques used to me...
Latent variable models are commonly used in medical statistics, although often not referred to under...
Latent variable models are commonly used in medical statistics, although often not referred to under...
Latent variable models are commonly used in medical statistics, although often not referred to under...
Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor a...
Latent variable modelling has gradually become an integral part of mainstream statistics and is curr...
Latent variable modelling has gradually become an integral part of mainstream statistics and is curr...
This article gives an overview of statistical analysis with latent variables. Us-ing traditional str...
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces...
In the thesis, we assess the use of latent vari able models applied to diagnostic accuracy and dis e...
In clinical research, interest sometimes lies in analysing variables which are not measured directly...
This edited volume features cutting-edge topics from the leading researchers in the areas of latent ...
This edited volume features cutting-edge topics from the leading researchers in the areas of latent ...
Many applications of biomedical science involve unobservable constructs, from measurement of health ...
Although statistical models serve as the foundation of data analysis in clinical studies, their inte...
Abstract Background Structural equation modeling (SEM) is a set of statistical techniques used to me...
Latent variable models are commonly used in medical statistics, although often not referred to under...
Latent variable models are commonly used in medical statistics, although often not referred to under...
Latent variable models are commonly used in medical statistics, although often not referred to under...
Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor a...
Latent variable modelling has gradually become an integral part of mainstream statistics and is curr...
Latent variable modelling has gradually become an integral part of mainstream statistics and is curr...
This article gives an overview of statistical analysis with latent variables. Us-ing traditional str...
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces...
In the thesis, we assess the use of latent vari able models applied to diagnostic accuracy and dis e...
In clinical research, interest sometimes lies in analysing variables which are not measured directly...
This edited volume features cutting-edge topics from the leading researchers in the areas of latent ...
This edited volume features cutting-edge topics from the leading researchers in the areas of latent ...
Many applications of biomedical science involve unobservable constructs, from measurement of health ...
Although statistical models serve as the foundation of data analysis in clinical studies, their inte...
Abstract Background Structural equation modeling (SEM) is a set of statistical techniques used to me...