The generalized linear mixed model (GLIMMIX) provides a powerful technique to model correlated outcomes with different types of distributions. The model can now be easily implemented with SAS PROC GLIMMIX in version 9.1. For binary outcomes, linearization methods of penalized quasi-likelihood (PQL) or marginal quasi-likelihood (MQL) provide relatively accurate variance estimates for fixed effec...

analysis of variance (ANOVA): one-way nested, hierarchical two-way linear model fixed, random, and mixed models factorial arrangement of treatments variance components sum of squares, mean square, expected mean square sampling fraction, fixed effects, random effects simple effects, main effects, interaction effects, additive effects analysis of covariance, covariate, concomitant variable data t...

We extend the family of multivariate generalized linear mixed models to include random effects that are generated by smooth densities. We consider two such families of densities, the so-called semi-nonparametric (SNP) and smooth nonparametric (SMNP) densities. Maximum likelihood estimation, under either the SNP or the SMNP densities, is carried out using a Monte Carlo EM algorithm. This algorit...

T his article challenges Fixed Effects (FE) modeling as the ‘default’ for time-series-crosssectional and panel data. Understanding different within and between effects is crucial when choosing modeling strategies. The downside of Random Effects (RE) modeling— correlated lower-level covariates and higher-level residuals—is omitted-variable bias, solvable with Mundlak’s (1978a) formulation. Conse...

The article consists of two parts. Part I examines the Chinese Annual Survey of Industrial Firms database (CASIF). We start with a brief description of the coverage and key variables, followed by a review of recent applications of the data set in empirical studies. We then discuss the quality and the limitations of the dataset and propose a data cleaning procedure that identifies the key inform...

PEER EFFECTS IN SEXUAL INITIATION: SEPARATING SOCIAL NORMS AND PARTNER SUPPLY Seth O. Richards Kenneth I. Wolpin Sexual activity among adolescents is associated with risks such as pregnancy and STDs, and there is substantial policy interest in how peers influence the timing of sexual initiation. This paper measures separate effects for two social mechanisms— peer-group norms and partner availab...

In longitudinal studies, mixed-effects models are important for addressing subject-specific effects. However, most existing approaches assume a normal distribution for the random effects, and this could affect the bias and efficiency of the fixed-effects estimator. Even in cases where the estimation of the fixed effects is robust with a misspecified distribution of the random effects, the estim...

The prevailing theorizing of globalization’s influence of human well-being suggests to assess both the favorable and unfavorable outcomes. This study formulates a dialectical model, adopts a comprehensive globalization measure and uses a three-wave panel data during 1980-2000 to empirically test direct and indirect effects of global flows’ human consequences. The outcomes from random effect mod...

Parametric nonlinear mixed effects models (NLMEs) are now widely used in biometrical studies, especially in pharmacokinetics research and HIV dynamics models, due to, among other aspects, the computational advances achieved during the last years. However, this kind of models may not be flexible enough for complex longitudinal data analysis. Semiparametric NLMEs (SNMMs) have been proposed by Ke ...