May 19, 2011
Levy, R., & Hancock, G. (2011). An Extended Model Comparison Framework for Covariance and Mean Structure Models, Accommodating Multiple Groups and Latent Mixtures Sociological Methods & Research, 40 (2), 256-278 DOI: 10.1177/0049124111404819
Roy Levy, Arizona State University, Tempe, AZ, USA, firstname.lastname@example.org
February 7, 2010
Jaak B. Billiet and Eldad Davidov Testing the Stability of an Acquiescence Style Factor Behind Two Interrelated Substantive Variables in a Panel Design Sociological Methods & Research 2008 36: 542-562.
This article addresses the question of to what extent one type of response style, called acquiescence (or agreeing response bias), is stable over time. A structural equation modeling approach Read the rest of this entry »
February 7, 2010
Least absolute deviation (LAD) is a well-known criterion to fit statistical models, but little is known about LAD estimation in structural equation modeling (SEM). To address this gap, the authors use the LAD criterion in SEM by minimizing the sum of the absolute deviations between the observed and the model-implied covariance matrices. Using Monte Carlo simulations, the authors compare the performance of this LAD estimator along several dimensions (bias, efficiency, convergence, frequencies of improper solutions, and absolute percentage deviation) to the full informationmaximum likelihood (ML) and unweighted least squares (ULS) estimators in structural equation modeling. The results for LAD are mixed: There are special conditions under which the LAD estimator outperforms ML and ULS, but the simulation evidence does not support a general claim that LAD is superior to ML and ULS in small samples.
Key Words: least absolute deviation • structural equation modeling • robust estimation • small sample research