Title of Dissertation: THE IMPACT OF MODEL SELECTION ON LOGLINEAR ANALYSIS OF CONTINGENCY TABLES Jing Gao, Doctor of Philosophy, 2009 Dissertation directed by: Professor C. Mitchell Dayton Department of Measurement, Statistics and Evaluation It is common practice for researchers in the social sciences and education to use model selection techniques to search for best fitting models and to carry...

A general framework is presented for the analysis of partially ordered set (poset) data. The work is motivated by the need to analyse poset data such as multi-componential responses in psychological measurement and partially accomplished cognitive tasks in educational measurement. It is shown how the generalized loglinear model can be used to represent poset data that form a lattice and how lat...

We set out IDR as a loglinear model-based Moran’s I test for Poisson count data that resembles the Moran’s I residual test for Gaussian data. We evaluate its type I and type II error probabilities via simulations, and demonstrate its utility via a case study. When population sizes are heterogeneous, IDR is effective in detecting local clusters by local association terms with an acceptable type ...

Within the framework of an n-commodity, n-factor, K-country loglinear model with identical Cobb–Douglas production coefficients and identical consumer-expenditure shares across countries, balanced trade, and a pattern of world endowments permitting positive outputs of all commodities in each country, it is shown that, given any mode of aggregating the n commodities into at most n − 1 industrial...

This paper aims at introducing the R package prefmod (Hatzinger, 2009) which allows the user to fit various models to paired comparison data. These models give estimated overall rankings of objects or items where each subject (respondent/judge) makes one or more comparisons between pairs of objects (items). The focus is on the loglinear Bradley-Terry (LLBT) model, the loglinear formulation of t...

Recent work on loglinear models in proba-bilistic constraint logic programming is applied to rst-order probabilistic reasoning. Probabilities are deened directly on the proofs of atomic formulae, and by marginal-isation on the atomic formulae themselves. We use Stochastic Logic Programs (SLPs) composed of labelled and unlabelled deenite clauses to deene the proof probabilities. We have a conser...