Whenever one uses ordinary least squares regression, one is making an implicit assumption that all of the independent variables have been measured without error. Such an assumption is obviously unrealistic for most social data. One approach for estimating such regression models is to measure implied coefficients between latent variables for which…

This working paper contains the overheads used in a seminar designed to introduce some basic concepts of statistics to nonstatisticians. The seminar has been presented on several occasions. The first part of the seminar, and the first set of overheads, deals with the essentials of statistics, including: (1) population, sample, and inference; (2)…

Direct and indirect effects in decomposed zero-order correlations among variables in causal models are considered. Under certain circumstances, the components of the decompositions could be interpreted as direct, indirect, and spurious causal effects, plus a component called joint associations. The sum of the direct and indirect effects is the…

Aside from the theoretical issues involving the validity of inferences from surveys, the basic problem of producinq unbiased estimates of regression parameters and estimates of the associated standard errors has been a particularly difficult issue in dealing with results from stratified multistage sample designs such as the one used in the…

This guidebook is designed for data analysts who are working with computer data files that contain records with incomplete data. It indicates choices the analyst must make and the criteria for making those choices in regard to the following questions: (1) What resources are available for performing the imputation? (2) How big is the data file? (3)…