Benchmark Analysis: Shopping with Proper Confidence

We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.     

Modelling data from single-photon emission computerized tomography

The completely random character of radioactive disintegration provides the basis of a strong justification for a Poisson linear model for single-photon emission computed tomography data, which can be used to produce reconstructions of isotope densities, whether by maximum likelihood or Bayesian methods. However, such a model requires the construction of a matrix of weights, which represent the mean rates of arrival at each detector of photons originating from each point within the body space. Two methods of constructing these weights are discussed, and reconstructions resulting from phantom and real data are presented.     

MEANINGFUL REGRESSION AND ASSOCIATION MODELS FOR CLUSTERED ORDINAL DATA

Many proposed methods for analyzing clustered ordinal data focus on the regression model and consider the association structure within a cluster as a nuisance. However, the association structure is often of equal interest—for example, temporal association in longitudinal studies and association between responses to similar questions in a survey. We discuss the use, appropriateness, and interpretability of various latent variable and Markov models for the association structure and propose a new structure that exploits the ordinality of the response. The models are illustrated with a study concerning opinions regarding government spending and an analysis of stability and change in teenage marijuana use over time, where we reveal different behavioral patterns for boys and girls through a comprehensive investigation of individual response profiles.     

National survey evidence on disasters and relief: Risk beliefs, self-interest, and compassion

A nationally representative sample of respondents estimated their fatality risks from four types of natural disasters, and indicated whether they favored governmental disaster relief. For all hazards, including auto accident risks, most respondents assessed their risks as being below average, with one-third assessing them as average. Individuals from high-risk states, or with experience with disasters, estimate risks higher, though by less than reasonable calculations require. Four-fifths of our respondents favor government relief for disaster victims, but only one-third do for victims in high-risk areas. Individuals who perceive themselves at higher risk are more supportive of government assistance.     

Compatibility,Leisure, and Satisfaction in Marital Relationships

This study challenges the prevailing view that marital companionship promotes marital satisfaction. By following a cohort of married couples for over a decade and by incorporating several methodological improvements—such as refining the measurement of marital satisfaction, determining how much spouses enjoy doing the leisure activities they pursue together and apart, and using diary data to portray marital leisure patterns—we found that the association between companionship and satisfaction is less robust than previously believed, and that it depends on how often spouses pursue activities that reflect their own and their partner's leisure preferences. Over time, involvement in leisure liked by husbands but disliked by wives, whether as a couple or by husbands alone, is both a cause and a consequence of wives' dissatisfaction.