For analyzing item response data, item response theory (IRT) models treat the discrete responses to the items as driven by underlying continuous latent traits, and consider the form of conditional probability of the response to each item given the latent traits. In a similar fashion, log-linear...

Modeling the processes underlying social network and attribute change allows researchers to better identify and understand dependencies present amongactors — people, places, or things. The connections that exist among these actors change over time, depend on the presence or absence of other...

The approach described in this talk starts with Bock's (1972) nominal response model (NRM). The NRM is a multinomial logistic regression model for responses to items where the ordering of response options is not known a priori and the predictor or explanatory variable is unobserved (i.e., the...

Given the rapid advancement of computer technology, the importance of administeringadaptive tests with polytomous items is in great need. With regard to the applicability ofadaptive testing using polytomous IRT models, adaptive testing can use polytomous items of either rating scales, or in some...

This article provides a largely nontechnical discussion of the acquisition of membership values in fuzzy set analyses. First the basic properties of a membership are discussed. Then the three common strategies of membership assignment—direct subjective assignment, indirect subjective...

The methodology described here is designed for social networks and is based on the research of Holland and Leinhardt, Wasserman and Iacobucci, and Many others. Holland and Leinhardt termed the simplest model from their family of log-linear models p1. The models presented in this article are not...