Sociologists increasingly face choices among competing algorithms that represent reasonable approaches to the same task, with little guidance in choosing among them. We develop a strategy that uses simulated data to identify the conditions under which different methods perform well and applies what is learned from the simulations to predict which…

In this article, I present a new multivariate regression model for analyzing outcomes with network dependence. The model is capable to account for two types of outcome dependence including the mean dependence that allows the outcome to depend on selected features of a known dependence network and the error dependence that allows the outcome to be…

Development of graphical methods for representing data has not kept up with progress in statistical techniques. This article presents a brief history of graphical representations of research findings and makes the case for a revival of methods developed in the early and mid-twentieth century, notably ISOTYPE and Chernoff's faces. It resurrects and…

The Cox proportional hazards model has been pervasively used in many social science areas to examine the effects of covariates on timing to an event. The standard Cox model is intended to study univariate survival data where there is a singular event of interest, which can only be experienced once. However, we may additionally wish to explore a…

Survey data are usually of mixed type (quantitative, multistate categorical, and/or binary variables). Multidimensional scaling (MDS) is one of the most extended methodologies to visualize the profile structure of the data. Since the past 60s, MDS methods have been introduced in the literature, initially in publications in the psychometrics area.…

In its standard formulation, sequence analysis aims at finding typical patterns in a set of life courses represented as sequences. Recently, some proposals have been introduced to jointly analyze sequences defined on different domains (e.g., work career, partnership, and parental histories). We introduce measures to evaluate whether a set of…

It is necessary to test for equivalence of measurements across groups to guarantee that comparisons of regression coefficients or mean scores of a latent factor are meaningful. Unfortunately, when tested, many scales display nonequivalence. Several researchers have suggested that nonequivalence may be used as a useful source of information as to…

Measuring values in sociological research sometimes involves the use of ranking data. A disadvantage of a ranking assignment is that the order in which the items are presented might influence the choice preferences of respondents regardless of the content being measured. The standard procedure to rule out such effects is to randomize the order of…

Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…

We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…