A Latent Class Binomial Logit Methodology for the Analysis of Paired Comparison Choice Data

A latent class model for identifying classes of subjects in paired comparison choice experiments is developed. The model simultaneously estimates a probabilistic classification of subjects and the logit models' coefficients relating characteristics of objects to choices for each respective group among two alternatives in paired comparison experiments. A modest Monte Carlo analysis of algorithm performance is presented. The proposed model is illustrated with empirical data from a consumer psychology experiment that examines the determinants of perceived consumer risk. The predictive validity of the method is assessed and compared to that of several other procedures. The sensitivity of the method to (randomly) eliminate comparisons, which is important in view of reducing respondent fatigue in the task, is investigated.     

An empirical comparison of EM,SEM and MCMC performance for problematic Gaussian mixture likelihoods

We compare EM, SEM, and MCMC algorithms to estimate the parameters of the Gaussian mixture model. We focus on problems in estimation arising from the likelihood function having a sharp ridge or saddle points. We use both synthetic and empirical data with those features. The comparison includes Bayesian approaches with different prior specifications and various procedures to deal with label switching. Although the solutions provided by these stochastic algorithms are more often degenerate, we conclude that SEM and MCMC may display faster convergence and improve the ability to locate the global maximum of the likelihood function.     

Ladies,we've been framed

If an individual is to act with proper demeanor and show proper deference, then it will be necessary for [her] to have areas of self-determination. [She] must have an expendable supply of the small indulgences which [her] society employs in its idiom of regard-such as cigarettes to give, chairs to proffer, food to provide, and so forth. [She] must have freedom of bodily movement so that it will be possible for [her] to assume a stance that conveys appropriate respect for others and appropriate demeanor on [her] own partErving Goffman, The Arrangement between the Sexes, Theory and Society 4, 3 (Fall 1977), pp. 301–331. I would like to acknowledge the helpful comments on earlier versions of this critique provided by Joan Roberts, Shepard Holdervy, Judith-Maris Hess Buechler, and Hans Buechler.     

An Exponential-Family Multidimensional Scaling Mixture Methodology

A multidimensional scaling methodology (STUNMIX) for the analysis of subjects' preference/choice of stimuli that sets out to integrate the previous work in this area into a single framework, as well as to provide a variety of new options and models, is presented. Locations of the stimuli and the ideal points of derived segments of subjects on latent dimensions are estimated simultaneously. The methodology is formulated in the framework of the exponential family of distributions, whereby a wide range of different data types can be analyzed. Possible reparameterizations of stimulus coordinates by stimulus characteristics, as well as of probabilities of segment membership by subject background variables, are permitted. The models are estimated in a maximum likelihood framework. The performance of the models is demonstrated on synthetic data, and robustness is investigated. An empirical application is provided, concerning intentions to buy portable telephones.