Many questions in social research must be evaluated over time. For example, in studies of intragenerational mobility, measuring opportunity for economic advancement requires longitudinal data. The authors develop and use a class of hybrid functional models to demonstrate how different models can...

type="main" xml:id="rssa12067-abs-0001" <title type="main">Summary</title> <p>We propose a log-linear model to assess the consistency of ego reports of dyadic outcomes. We do so specifically in the context where males and females report on shared events, and we demonstrate how inconsistencies can be assessed by using a...</p>

type="main" xml:id="rssb12014-abs-0001" <title type="main">Summary</title> <p>Models of dynamic networks—networks that evolve over time—have manifold applications. We develop a discrete time generative model for social network evolution that inherits the richness and flexibility of the class of exponential family...</p>

The ability to simulate graphs with given properties is important for the analysis of social networks. Sequential importance sampling has been shown to be particularly effective in estimating the number of graphs adhering to fixed marginals and in estimating the null distribution of graph...

latentnet is a package to fit and evaluate statistical latent position and cluster models for networks. Hoff, Raftery, and Handcock (2002) suggested an approach to modeling networks based on positing the existence of an latent space of characteristics of the actors. Relationships form as a...

Mixture models have been popular in the literature of both statistics and social science. In this dissertation, we propose a new mixture model, namely, nonparametric finite mixture of regression models, which can be viewed as a natural extension of finite mixture of linear regression. In the...

In this dissertation, several new statistical procedures in nonparametric and semiparametric models are proposed. The concerns of the research are efficiency, robustness and sparsity.In Chapter 3, we propose complete composite quantile regression (CQR) procedures for estimating both the...