In this talk, I introduce the main ideas of structural equation models (SEMs) with latent variables and Stata tools that can be used for such models. The two approaches most often used in applied work are numeric integration of the latent variables and covariance structure modeling. The first...

Eliciting truthful answers to sensitive questions is an age-old problem in survey research. Respondents tend to underreport socially undesired or illegal behaviors, while overreporting socially desirable ones. To combat such response bias, various techniques have been developed that are geared...

Despite its frequent use in applied work, nonparametric approaches to efficiency analysis, namely data envelopment analysis (DEA) and free disposal hull (FDH), have bad reputations among econometricians. This is mainly due to DEA and FDH representing deterministic approaches that are highly...

Fixed-effect models have become increasingly popular in the field of sociology. The possibility of controlling for unobserved heterogeneity makes these models a prime tool for causal analysis. As of today, fixed-effects models have been derived and implemented for many statistical software...

Stata has a rich set of operators for specifying factor variables in linear and nonlinear regression models. I will show how to test for the effects of factor variables in these models. I will also show how to compare and contrast these effects using linear combinations of the model coefficients.

In a series of recent articles, Karlson, Holm, and Breen have developed a method for comparing estimated coefficients of nested nonlinear probability models. The KHB method is a general decomposition method that is unaffected by the rescaling or attenuation bias that arises in cross- model...

Although cluster–robust standard errors are now recognized as essential in a panel-data context, official Stata only supports clusters that are nested within panels. This rules out the possibility of defining clusters in the time dimension, and modeling contemporaneous dependence of panel...

The logit model is a widely used regression technique in social research. However, the use and interpretation of coefficients from logit models have proven contentious. Problems arise because the mean and the variance of discrete variables cannot be separated. Logit coefficients are identified...

Currently, we observe in the social and behavioral sciences an increasing demand on complex longitudinal household survey data for national and cross-national analyses. The state of the art (for national as well as international comparative data collections) provides two types of solutions:...