Under this identifiability assumption, the convergence of the EMS algorithm for latent variable selection in the multidimensional two鈥恜arameter logistic (M2PL) models can be verified. We give an efficient implementation of the EMS for the M2PL models. Simulation studies show that the EMS ...
Latent Variable Models Under Misspecification: Two-Stage Least Squares (2SLS) and Maximum Likelihood (ML) Estimators This article compares maximum likelihood (ML) estimation to three variants of two-stage least squares (2SLS) estimation in structural equation models. The ... KA Bollen,JB Kirby,...
Latent variable modeling is a multivariate technique commonly used in the social and behavioral sciences. The models used in such analysis relate all obser... JC Eickhoff - 《Journal of Modern Applied Statistical Methods》 被引量: 0发表: 2005年 Maximum Likelihood Estimation of Two-Level Latent V...
We present a sequential Monte Carlo (SMC) method for maximum likelihood (ML) parameter estimation in latent variable models. Stan- dard methods rely on gradient algorithms such as the Expectation- Maximization (EM) algorithm and its Monte Carlo variants. Our approach is different and motivated by...
Latent variable models are used in biological and social sciences to investigate characteristics that are not directly measurable. The generation of individual scores of latent variables can simplify subsequent analyses. However, missing measurements in real data complicate the calculation of scores. Missing...
In this paper, we deal with the problem of modeling counterfactual reasoning in scenarios where, apart from the observed endogenous variables, we have a latent variable that affects the outcomes and, consequently, the results of counterfactuals queries (or simply conterfactuals). In this case, a...
Structural equation models with interaction and quadratic effects have become a standard tool for testing nonlinear hypotheses in the social sciences. Most of the current approache... 查看全部>> Augustin Kelava,Benjamin Nagengast 被引量: 0发表: 0年 Latent variable interaction and quadratic effect est...
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Summary Latent variable models provide a rich and widely-used collection of models that are especially suited for inference when the data are observed from experiments where more than one source of variability is present. Latent variable models include semi-parametric regression models, by virtue of ...
(Fig. 18.18). Cells may contain Schaumann andasteroid bodies, and confluent masses of granulomas may develop. Variable degrees of diffuseinterstitial fibrosisoccur, and large, hyalinized fibrotic nodules may be present. Sometimes after many years, only diffuse interstitial fibrosis is seen, without ...