We introduce a dynamic network model with probabilistic link functions that depend on stochastically time-varying parameters. We adopt the widely used blockmodel framework and allow the highdimensional vector of link probabilities to be a function of a low-dimensional set of dynamic factors. The...

This paper examines the finite sample properties of estimators for approximate factor models when N is small via simulation study. Although the “rule-of-thumb” for factor models does not support using approximate factor models when N is small, we find that the principal component analysis...

This paper considers the problem of making inferences about the effects of a program on multiple outcomes when the assignment of treatment status is imperfectly randomized. By imperfect randomization we mean that treatment status is reassigned after an initial randomization on the basis of...