ADDITIVE MODELS WITH PREDICTORS SUBJECT TO MEASUREMENT ERROR

This paper develops a likelihood‐based method for fitting additive models in the presence of measurement error. It formulates the additive model using the linear mixed model representation of penalized splines. In the presence of a structural measurement error model, the resulting likelihood involves intractable integrals, and a Monte Carlo expectation maximization strategy is developed for obtaining estimates. The method's performance is illustrated with a simulation study.     

Religious affiliation and the family

The process of religious affiliation is mediated by institutions such as the family, which provide a network of ties to the public sphere. Variations in the likelihood of those with no religious affiliation in high school (N=900) becoming church members by the time they reach 30 are explained in terms of a combination of individual attributes, such as educational and spatial mobility, and changes in structural location, such as the transition to marital and parental status. Panel data from the Career Development Study show that women's chances of affiliation are more affected than are men's by parents' religious homogamy, getting married, and having children.     

Domains of convergence for the EM algorithm: a cautionary tale in a location estimation problem

The EM algorithm is a popular method for maximizing a likelihood in the presence of incomplete data. When the likelihood has multiple local maxima, the parameter space can be partitioned into domains of convergence, one for each local maximum. In this paper we investigate these domains for the location family generated by the t-distribution. We show that, perhaps somewhat surprisingly, these domains need not be connected sets. As an extreme case we give an example of a domain which consists of an infinite union of disjoint open intervals. Thus the convergence behaviour of the EM algorithm can be quite sensitive to the starting point.     

A theory of prudential values and a rule utilitarian theory of morality

Ethics can be divided into a theory of prudential values and a theory of morality in a narrower sense. My paper proposes a utilitarian — a rule-utilitarian — theory of morality. But it deviates from most of the utilitarian tradition by rejecting the hedonistic and subjectivistic accounts of prudential values favored by many utilitarian writers. While economists tend to define people's utility levels in terms of their actual preferences, ethics must define them in terms of their informed preferences. To prefer A over B does not mean to have a stronger desire for A than for B. Rather, it means to regard one's access to A as being more important than one's access to B. Even though different people often have quite different preferences, their basic desires seem to be much the same. We must choose our moral rules, and our society's moral code as a whole, by their social utility. An important factor in determining their social utility are their expectation effects. Unlike the rule — utilitarian more code, the act — utilitarian moral code would be unable to give proper weight to these expectation effects. It would also unduly restrict our individual freedom. Finally, I shall argue against Kant that morality is primarily a servant of many other human values rather than itself the highest value of human life.     

Characteristics of smokeless tobacco use among high school football players as related to type of smokeless tobacco and period of use.

The present study was conducted to assess differences in the behavioral and demographic characteristics of snuff (dip) users as compared to users of chewing tobacco. High School football players (1116) were surveyed concerning their use and perceptions of smokeless tobacco. Adolescent athletes who tried smokeless tobacco were more likely to be white, to use cigarettes, alcohol, and cigars and to have family users than those who never tried. Initial use was highest before the age of fourteen years and was influenced by friends, curiosity and family. Dippers tended to initiate use because of friends, while chewers started because of family users. Users of both dip and chew started primarily because of curiosity. Users of both were more likely to consume greater amounts to alcohol and cigarettes and to smoke cigars and pipes. It appears that the longer smokeless tobacco is consumed, the more likely both dip and chew will be used. Users of smokeless tobacco for more than two years tended to consume more of the product each week, used it for more hours/day, initiated use at an earlier age, and used it more often at school and work than those using it for less than two years. Use of cigars/pipes, consumption of alcohol, and quantity of cigarette consumption increased significantly with longer duration of smokeless tobacco use. Intervention and prevention programs would be helped by understanding differences between users of various smokeless tobacco products and differences related to the duration of use. In addition, further analyses of smokeless tobacco users should study chewers, dippers, and users of both separately.     

Significance of the Dermal Route of Exposure to Risk Assessment

The skin is a route of exposure that needs to be considered when conducting a risk assessment. It is necessary to identify the potential for dermal penetration by a chemical as well as to determine the overall importance of the dermal route of exposure as compared with inhalation or oral routes of exposure. The physical state of the chemical, vapor or liquid, the concentration, neat or dilute, and the vehicle, lipid or aqueous, is also important. Dermal risk is related to the product of the amounts of penetration and toxicity. Toxicity involves local effects on the skin itself and the potential for systemic effects. Dermal penetration is described in large part by the permeability constant. When permeability constants are not known, partition coefficients can be used to estimate a chemical's potential to permeate the skin. With these concepts in mind, a tiered approach is proposed for dermal risk assessment. A key first step is the determination of a skin-to-air or skin-to-medium partition coefficient to estimate a potential for dermal absorption. Building a physiologically-based pharmacokinetic (PBPK) model is another step in the tiered approach and is useful prior to classical in vivo toxicity tests. A PBPK model can be used to determine a permeability constant for a chemical as well as to show the distribution of the chemical systemically. A detailed understanding of species differences in the structure and function of the skin and how they relate to differences in penetration rates is necessary in order to extrapolate animal data from PBPK models to the human. A study is in progress to examine anatomical differences for four species.     

DO DRINKERS KNOW WHEN TO SAY WHEN? AN EMPIRICAL ANALYSIS OF DRUNK DRIVING

This paper presents empirical evidence that an individual's decision to drive while drunk is negatively affected by the expected full price of driving drunk. The analysis uses a unique data set containing information on self-reported drunk driving matched to state-level drunk driving policies as well as to state excise taxes on beer. These are hypothesized and found to affect drunk driving. Further, we find interesting racial differences but surprisingly small differences by gender in the effect of socioeconomic and policy variables on drunk driving propensities.     

Modelling map positional error to infer true feature location

The authors consider the issue of map positional error, or the difference between location as represented in a spatial database (i.e., a map) and the corresponding unobservable true location. They propose a fully model‐based approach that incorporates aspects of the map registration process commonly performed by users of geographic informations systems, including rubber‐sheeting. They explain how estimates of positional error can be obtained, hence estimates of true location. They show that with multiple maps of varying accuracy along with ground truthing data, suitable model averaging offers a strategy for using all of the maps to learn about true location.