Clinical psychology researchers studying adolescents and young adults long have been interested in characterizing the latent categorical (classes/profiles) versus continuous (factors) nature of psychological syndromes. To inform this debate, researchers sometimes compare the fit of finite mixture versus factor analysis models to symptom data. This study explains and evaluates how missing data h...

Genome wide complex trait analysis (GCTA) is extended to include environmental effects of the maternal genotype on offspring phenotype ("maternal effects", M-GCTA). The model includes parameters for the direct effects of the offspring genotype, maternal effects and the covariance between direct and maternal effects. Analysis of simulated data, conducted in OpenMx, confirmed that model parameter...

We examine properties of estimators of count data model with endogenous switching. The estimation of the count data model that accommodates endogenous switching can be accomplished by Full Information Maximum Likelihood (FIML). However, FIML estimation requires fully and correctly specified model and is computationally burdensome. Alternative estimation methods do not require fully specified mo...

A system of nonlinear biomass component equations was developed for slash pine (Pinus elliottii Engelm. var. elliottii) trees using an econometric approach in which endogenous right-hand-side variables were included some equations. The fitted to data from 306 sampled the southeastern United States with weighted two-stage (2SLS) and three-stage (3SLS) least squares full information maximum-likel...

The main purpose of this study is to improve estimation efficiency in obtaining fullinformation maximum likelihood (FIML) estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM; Cai, 2008, 2010a, 2010b). Results indicate that the MH-RM algorithm can produce FIML estimates and their standar...

Abstract Macroeconomic researchers use a variety of estimators to parameterise their models empirically. One such is FIML; another indirect inference (II). form ‘informal’ whereby data features are ‘targeted’ by the model — i.e. parameters chosen so that model-simulated replicate closely. Monte Carlo experiments show in small samples prevalent macro data, both FIML informal II produce high bias...

Simulated data, validity reports and a firefighter predictive validation study are used to examine bias created by three common selection problems-range restriction, applicant incumbent attrition, nonlinearity compression of high test scores. Top 20% samples drawn from an pool with known coefficients demonstrate that the sample estimates predictors differentially biased in both magnitude direct...