Topic
Latent variable model
About: Latent variable model is a research topic. Over the lifetime, 3589 publications have been published within this topic receiving 235061 citations.
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TL;DR: In this article, a latent class model is described in which the latent classes are ordered imposing inequality constraints on item response and cumulative response probabilities from subsequent latent classes, and an algorithm to obtain the maximum likelihood estimates of the model parameters is proposed and is applied to a real data set.
Abstract: In this paper a latent class model is described in which the latent classes are ordered imposing inequality constraints on item response and cumulative response probabilities from subsequent latent classes. These inequality constraints are derived from the basic assumption that, when the latent classes may be ordered from low to high along the latent continuum, the probability of a ‘positive’ response should increase monotonically as one moves along this continuum. An algorithm to obtain the maximum likelihood estimates of the model parameters is proposed and is applied to a real data set.
112 citations
01 Jan 2005
TL;DR: The linear factor analysis (FA) model is a popular tool for exploratory data analysis or, more precisely, for assessing the dimensionality of sets of items as mentioned in this paper, but it is often used for continuous observed indicators, yielding results that might be incorrect.
Abstract: The linear factor analysis (FA) model is a popular tool for exploratory data analysis or, more precisely, for assessing the dimensionality of sets of items. Although it is well known that it is meant for continuous observed indicators, it is often used with dichotomous, ordinal, and other types of discrete variables, yielding results that might be incorrect. Not only parameter estimates may be biased, but also goodness-of-fit indices cannot be trusted. Magidson and Vermunt (2001) presented a nonlinear factor-analytic model based on latent class (LC) analysis that is especially suited for dealing with categorical indicators, such as dichotomous, ordinal, and nominal variables,
112 citations
TL;DR: In this study, slow features as temporally correlated LVs are derived using probabilistic slow feature analysis to represent nominal variations of processes, some of which are potentially correlated to quality variables and hence help improving the prediction performance of soft sensors.
Abstract: Latent variable (LV) models provide explicit representations of underlying driving forces of process variations and retain the dominant information of process data In this study, slow features as temporally correlated LVs are derived using probabilistic slow feature analysis Slow features evolving in a state-space form effectively represent nominal variations of processes, some of which are potentially correlated to quality variables and hence help improving the prediction performance of soft sensors An efficient EM algorithm is proposed to estimate parameters of the probabilistic model, which turns out to be suitable for analyzing massive process data Two criteria are ∗To whom correspondence should be addressed †Tsinghua University ‡University of Alberta 1 also proposed to select quality-relevant slow features The validity and advantages of the proposed method are demonstrated via two case studies
111 citations
TL;DR: In this article, a method for interval estimation of scale reliability with discrete data is outlined, which is applicable with multi-item instruments consisting of binary measures, and is developed within the latent variable modeling methodology.
Abstract: A method for interval estimation of scale reliability with discrete data is outlined. The approach is applicable with multi-item instruments consisting of binary measures, and is developed within the latent variable modeling methodology. The procedure is useful for evaluation of consistency of single measures and of sum scores from item sets following the 2-parameter logistic model or the 1-parameter logistic model. An extension of the method is described for constructing confidence intervals of change in reliability due to instrument revision. The proposed procedure is illustrated with an example.
111 citations
TL;DR: In this article, an empirical investigation of the predictability and co-movement of risk premia in the term structure of Euromarket interest rates is presented, and it is shown that risk premias move in proportion to a single latent variable, which can be interpreted as a specialization of the ICAPM in which assets have constant betas on a single, unobservable benchmark portfolio.
111 citations