This paper will show the use of a latent variable model for binary data which allows information on the latent variable to be extracted from the pattern of the missing data. We use a modified version of the logit-probit model for binary data (Bartholomew, 1987) proposed by Knott, Albanese and Galbraith (1990). The model will be applied to data on racia
Latent variable models represent a useful tool for the analysis of complex data characterized by the...
This edited volume features cutting-edge topics from the leading researchers in the areas of latent ...
Latent variable models are widely used in social sciences for measuring constructs (latent variables...
When researchers are interested in measuring social phenomena that cannot be measured using a single...
Latent variable models are widely used in social sciences in which interest is centred on entities s...
Missing problem is very common in today's public health studies because of responses measured longit...
In recent years several authors have viewed latent trait models for binary data as special models fo...
In recent years several authors have viewed latent trait models for binary data as special models f...
Latent class models are widely used for analyzing correlated binary data. The underlying premise is ...
In Beunckens et al. (2006), we propose a so-called latent-class mixture model, bringing to-gether fe...
A two-dimensional IRT model is introduced for binary data in the presence of omitted responses. Its ...
This paper addresses the problem of comparing the fit of latent class and latent trait models when t...
Latent variable models are used extensively to explain association or correlation between observed o...
Most of the results in this thesis are obtained for the logit/probit model for binary response data ...
Latent trait shared-parameter mixed-models (LTSPMM) for ecological momentary assessment (EMA) data c...
Latent variable models represent a useful tool for the analysis of complex data characterized by the...
This edited volume features cutting-edge topics from the leading researchers in the areas of latent ...
Latent variable models are widely used in social sciences for measuring constructs (latent variables...
When researchers are interested in measuring social phenomena that cannot be measured using a single...
Latent variable models are widely used in social sciences in which interest is centred on entities s...
Missing problem is very common in today's public health studies because of responses measured longit...
In recent years several authors have viewed latent trait models for binary data as special models fo...
In recent years several authors have viewed latent trait models for binary data as special models f...
Latent class models are widely used for analyzing correlated binary data. The underlying premise is ...
In Beunckens et al. (2006), we propose a so-called latent-class mixture model, bringing to-gether fe...
A two-dimensional IRT model is introduced for binary data in the presence of omitted responses. Its ...
This paper addresses the problem of comparing the fit of latent class and latent trait models when t...
Latent variable models are used extensively to explain association or correlation between observed o...
Most of the results in this thesis are obtained for the logit/probit model for binary response data ...
Latent trait shared-parameter mixed-models (LTSPMM) for ecological momentary assessment (EMA) data c...
Latent variable models represent a useful tool for the analysis of complex data characterized by the...
This edited volume features cutting-edge topics from the leading researchers in the areas of latent ...
Latent variable models are widely used in social sciences for measuring constructs (latent variables...