The paper focuses on latent class models and their application for quantitative data. Latent class modeling is one of multivariate analysis techniques of the contingency table and can be viewed as a special case of model-based clustering, for multivariate discrete data. It is assumed that each observation comes from one of the numbers of subpopulations, with its own probability distribution. We used latent class analysis for grouping and detecting homogeneity of Silesian people using poLCA package of R. We analyzed data collected by the Department of Social Pedagogy, University of Silesia in Katowice
In social sciences, especially in economy, to reveal relations between variables it’s easy to apply...
Latent class analysis (LCA) for categorical data is a model-based clustering and classification tech...
International audienceThis chapter deals with mixture models for clustering categorical and mixed-ty...
The paper focuses on latent class models and it's application for quantitative data. Latent class mo...
In latent class analysis it is assumed that each observation comes from one of a number of classes (...
This halfday short course introduces the concept of latent class analysis, which is a model-based st...
Item response theory is considered to be one of the two trends in methodological assessment of the r...
The thesis "The Potential of Latent Class Analysis: the Czech Television Audience Case Study" deals ...
Latent tree analysis seeks to model the correlations amonga set of random variables using a tree of ...
Latent class analysis has been widely used in the measurement models. Models based on latent variabl...
In this paper Latent Class Analysis is applied on two different data sets. One of which is of electi...
Latent class analysis (LCA) is a statistical method used to group individuals (cases, units) into cl...
to longitudinal data assumes homogeneity of change over persons. Using latent class models, several ...
Researchers use latent class (LC) analysis to derive meaningful clusters from sets of categorical va...
Latent class analysis can be viewed as a special case of model–based clustering for multivariate dis...
In social sciences, especially in economy, to reveal relations between variables it’s easy to apply...
Latent class analysis (LCA) for categorical data is a model-based clustering and classification tech...
International audienceThis chapter deals with mixture models for clustering categorical and mixed-ty...
The paper focuses on latent class models and it's application for quantitative data. Latent class mo...
In latent class analysis it is assumed that each observation comes from one of a number of classes (...
This halfday short course introduces the concept of latent class analysis, which is a model-based st...
Item response theory is considered to be one of the two trends in methodological assessment of the r...
The thesis "The Potential of Latent Class Analysis: the Czech Television Audience Case Study" deals ...
Latent tree analysis seeks to model the correlations amonga set of random variables using a tree of ...
Latent class analysis has been widely used in the measurement models. Models based on latent variabl...
In this paper Latent Class Analysis is applied on two different data sets. One of which is of electi...
Latent class analysis (LCA) is a statistical method used to group individuals (cases, units) into cl...
to longitudinal data assumes homogeneity of change over persons. Using latent class models, several ...
Researchers use latent class (LC) analysis to derive meaningful clusters from sets of categorical va...
Latent class analysis can be viewed as a special case of model–based clustering for multivariate dis...
In social sciences, especially in economy, to reveal relations between variables it’s easy to apply...
Latent class analysis (LCA) for categorical data is a model-based clustering and classification tech...
International audienceThis chapter deals with mixture models for clustering categorical and mixed-ty...