WHOSE MODEL IS IT!: BRIDGING THE GAP BETWEEN ENGINEERING AND STATISTICS

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71421/1/j.1747-1567.1999.tb01539.x.pd

Bayesian Estimation of Circumplex Models Subject to Prior Theory Constraints and Scale-Usage Bias

This paper presents a hierarchical Bayes circumplex model for ordinal ratings data. The circumplex model was proposed to represent the circular ordering of items in psychological testing by imposing inequalities on the correlations of the items. We provide a specification of the circumplex, propose identifying constraints and conjugate priors for the angular parameters, and accommodate theory-driven constraints in the form of inequalities. We investigate the performance of the proposed MCMC algorithm and apply the model to the analysis of value priorities data obtained from a representative sample of Dutch citizens.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43547/1/11336_2001_Article_958.pd

Adjusting Choice Models to Better Predict Market Behavior

The emergence of Bayesian methodology has facilitated respondent-level conjoint models, and deriving utilities from choice experiments has become very popular among those modeling product line decisions or new product introductions. This review begins with a paradox of why experimental choices should mirror market behavior despite clear differences in content, structure and motivation. It then addresses ways to design the choice tasks so that they are more likely to reflect market choices. Finally, it examines ways to model the results of the choice experiments to better mirror both underlying decision processes and potential market choices.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47012/1/11002_2005_Article_5885.pd

Discrete and Continuous Representations of Unobserved Heterogeneity in Choice Modeling

We attempt to provide insights into how heterogeneity has been and can be addressed in choice modeling. In doing so, we deal with three topics: Models of heterogeneity, Methods of estimation and Substantive issues. In describing models we focus on discrete versus continuous representations of heterogeneity. With respect to estimation we contrast Markov Chain Monte Carlo methods and (simulated) likelihood methods. The substantive issues discussed deal with empirical tests of heterogeneity assumptions, the formation of empirical generalisations, the confounding of heterogeneity with state dependence and consideration sets, and normative segmentation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46977/1/11002_2004_Article_230988.pd

Three-dimensional structure of a viral genome-delivery portal vertex.

DNA viruses such as bacteriophages and herpesviruses deliver their genome into and out of the capsid through large proteinaceous assemblies, known as portal proteins. Here, we report two snapshots of the dodecameric portal protein of bacteriophage P22. The 3.25-Å-resolution structure of the portal-protein core bound to 12 copies of gene product 4 (gp4) reveals a ~1.1-MDa assembly formed by 24 proteins. Unexpectedly, a lower-resolution structure of the full-length portal protein unveils the unique topology of the C-terminal domain, which forms a ~200-Å-long α-helical barrel. This domain inserts deeply into the virion and is highly conserved in the Podoviridae family. We propose that the barrel domain facilitates genome spooling onto the interior surface of the capsid during genome packaging and, in analogy to a rifle barrel, increases the accuracy of genome ejection into the host cell

Inferring Market Structure from Customer Response to Competing and Complementary Products

We consider customer influences on market structure, arguing that market structure should explain the extent to which any given set of market offerings are substitutes or complements. We describe recent additions to the market structure analysis literature and identify promising directions for new research in market structure analysis. Impressive advances in data collection, statistical methodology and information technology provide unique opportunities for researchers to build market structure tools that can assist “real-time” marketing decision-making.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46981/1/11002_2004_Article_5088105.pd

Bayesian inference for finite mixtures of generalized linear models with random effects

We present an hierarchical Bayes approach to modeling parameter heterogeneity in generalized linear models. The model assumes that there are relevant subpopulations and that within each subpopulation the individual-level regression coefficients have a multivariate normal distribution. However, class membership is not known a priori, so the heterogeneity in the regression coefficients becomes a finite mixture of normal distributions. This approach combines the flexibility of semiparametric, latent class models that assume common parameters for each sub-population and the parsimony of random effects models that assume normal distributions for the regression parameters. The number of subpopulations is selected to maximize the posterior probability of the model being true. Simulations are presented which document the performance of the methodology for synthetic data with known heterogeneity and number of sub-populations. An application is presented concerning preferences for various aspects of personal computers.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45757/1/11336_2005_Article_BF02294188.pd

A comparison of generalized multinomial logit (GMNL) and latent class approaches to studying consumer heterogeneity with some extensions of the GMNL model by Peter J. Lenk

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/89466/1/asmb941.pd

Bayesian estimation of circumplex models subject to prior theory constraints and scale-usage bias

http://deepblue.lib.umich.edu/bitstream/2027.42/35834/2/b2110751.0001.001.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/35834/1/b2110751.0001.001.tx