A Three-Dimensional Latent Variable Model for Attitude Scales

February 7, 2010

Shing-On Leung A Three-Dimensional Latent Variable Model for Attitude Scales  Sociological Methods & Research 2008 37: 135-154.

The author proposes a three-dimensional latent variable (trait) model for analyzing attitudinal scaled data. It is successfully applied to two examples: one with 12 binary items and the other with 8 items of five categories each. The models are exploratory instead of confirmatory, Read the rest of this entry »

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Kenneth A. Bollen, James B. Kirby, Patrick J. Curran, Pamela M. Paxton, and Feinian Chen Latent Variable Models Under Misspecification: Two-Stage Least Squares (2SLS) and Maximum Likelihood (ML) Estimators Sociological Methods & Research 2007 36: 48-86

February 7, 2010

This article compares maximum likelihood (ML) estimation to three variants of two-stage least squares (2SLS) estimation in structural equation models. The authors use models that are both correctly and incorrectly specified. Simulated data are used to assess bias, efficiency, and accuracy of hypothesis tests. Generally, 2SLS with reduced sets of instrumental variables performs similarly to ML when models are correctly specified. Under correct specification, both estimators have little bias except at the smallest sample sizes and are approximately equally efficient. As predicted, when models are incorrectly specified, 2SLS generally performs better, with less bias and more accurate hypothesis tests. Unless a researcher has tremendous confidence in the correctness of his or her model, these results suggest that a 2SLS estimator should be considered.

Key Words: 2SLS • misspecification • latent variable models • structural equation models • FIML • specification error