This paper studies simultaneous equations models for two or more discrete outcomes. These models may be incoherent, delivering no values of the outcomes at certain values of the latent variables and covariates, and they may be incomplete, delivering more than one value of the outcomes at certain values of the covariates and latent variates. We revisit previous approaches to the problems of inco...

We develop a personalized real-time risk scoring algorithm that provides timely and granular assessments for the clinical acuity of ward patients based on their (temporal) lab tests and vital signs. Heterogeneity of the patients’ population is captured via a hierarchical latent class model; the proposed algorithm aims to “discover” the number of latent classes in the patients’ population, and t...

An overview is provided of recent developments in the use of latent class (LC) models in social science research. Special attention is paid to the application of LC analysis as a factor-analytic tool and as a tool for random-effects modeling. Furthermore, an extension of the LC model to deal with nested data structures is presented.

This paper discusses alternatives to single-step mixture modeling. A 3step method for latent class predictor variables is studied in several different settings including latent class analysis, latent transition analysis, and growth mixture modeling. It is explored under violations of its assumptions such as with direct effects from predictors to latent class indicators. The 3-step method is als...

【キーワード】C25, C93, D12, Q49, Energy efficiency label, Consumers’ purchase decision, Latent class model, Willingness to pay, China 【要約】In this paper we apply hypothetical choice experiments through a field survey in Shanghai of China to examine whether China Energy Efficiency Label affects consumers’ choices of air conditioner and refrigerator. A latent class approach is used to observe both heter...

The latent structure of antisocial personality disorder (ASPD) and psychopathy has been examined using both Meehl’s taxometric method and other latent variable models, yielding results that have not been entirely consistent. However, in each instance, researchers used independent data sets for their analyses, obscuring whether the inconsistent findings resulted from the analytic method or from ...

poLCA is a software package for the estimation of latent class and latent class regression models for polytomous outcome variables, implemented in the R statistical computing environment. Both models can be called using a single simple command line. The basic latent class model is a finite mixture model in which the component distributions are assumed to be multi-way cross-classification tables...

This paper presents a general approach to the analysis of categorical panel data which is based on using causal log-linear models with latent variables. Like the well-known LISREL model, these models consist of a structural and a measurement part. In the structural part, a system of logit equations is used to explain changes which occur in the dependent variable of interest. An unrestricted or ...