Development and correlates of alcohol use from ages 13-20

This study examined alcohol use development from ages 13-20 years. The sample comprised 256 youth (50.4% female; 51.2% White, 48.8% African American) assessed annually for 6 years. A cohort-sequential latent growth model was used to model categorical alcohol use (non-use vs. use). Covariates included gender, race, income, parent marital status, risk taking, spiritual beliefs, parent alcohol use, family alcohol problems, family cohesion, friends' alcohol use, and normative peer use. The alcohol use trajectory increased steadily with age. Risk taking, friends' alcohol use, and normative peer use were positively associated with higher initial rates of alcohol use. Initial parent alcohol use and positive change in parents' and friends' alcohol use over time were related to an increase in alcohol use from ages 13-20 years.     

Migration,Social Networks,and Child Health in Mexican Families

This paper examines the consequences of parental migratory strategies for children in three types of Mexican families: those living with their migrant parents in the United States, those living with parents who migrated and returned to Mexico, and those living in Mexico with parents who have never migrated. Using data on 804 children from the Health and Migration Survey (HMS), we found significant differences in children's health across the three types of families. Results also revealed robust effects on child health of the size of immediate and extended social networks and migration experience after controlling for potential mediators such as mother's general health, receipt of social support, and child's age and sex. Findings suggest that social networks and migration affect children in complex ways, offering health benefits to those with migrant parents in U.S. households but not to those living with parents who migrated in the past and returned to Mexico.     

Multistage sampling for latent variable models

I consider the design of multistage sampling schemes for epidemiologic studies involving latent variable models, with surrogate measurements of the latent variables on a subset of subjects. Such models arise in various situations: when detailed exposure measurements are combined with variables that can be used to assign exposures to unmeasured subjects; when biomarkers are obtained to assess an unobserved pathophysiologic process; or when additional information is to be obtained on confounding or modifying variables. In such situations, it may be possible to stratify the subsample on data available for all subjects in the main study, such as outcomes, exposure predictors, or geographic locations. Three circumstances where analytic calculations of the optimal design are possible are considered: (i) when all variables are binary; (ii) when all are normally distributed; and (iii) when the latent variable and its measurement are normally distributed, but the outcome is binary. In each of these cases, it is often possible to considerably improve the cost efficiency of the design by appropriate selection of the sampling fractions. More complex situations arise when the data are spatially distributed: the spatial correlation can be exploited to improve exposure assignment for unmeasured locations using available measurements on neighboring locations; some approaches for informative selection of the measurement sample using location and/or exposure predictor data are considered.     

Mothers and child care: policies,values and theories

Government expansion of child care services is based on the assumption that both parents are employed (the adult worker model) and make cost‐benefit calculations in choosing child care (the rational economic choice model). This paper addresses this assumption, based on research examining mothers' assessments of appropriate child care. These assessments involve complex moral and emotional decisions around their own and their children's needs, and differ between social groups. On this basis, we conclude that the assumptions underlying current child care expansion policy are inadequate, and that the mere expansion of services is not enough.     

Forecasting the Penetration of a New Product—A Bayesian Approach

We adopt a Bayesian approach to forecast the penetration of a new product into a market. We incorporate prior information from an existing product and/or management judgments into the data analysis. The penetration curve is assumed to be a nondecreasing function of time and may be under shape constraints. Markov-chain Monte Carlo methods are proposed and used to compute the Bayesian forecasts. An example on forecasting the penetration of color television using the information from black-and-white television is provided. The models considered can also be used to address the general bioassay and reliability stress-testing problems.     

Ranked-Weighted Utilities and Qualitative Convolution

For gambles—non-numerical consequences attached to uncertain chance events—analogues are proposed for the sum of independent random variables and their convolution. Joint receipt of gambles is the analogue of the sum of random variables. Because it has no unique expansion as a first-order gamble analogous to convolution, a definition of qualitative convolution is proposed. Assuming ranked, weighted-utility representations (RWU) over gains (and, separately, over losses, but not mixtures of both), conditions are given for the equivalence of joint receipt, qualitative convolution, and a utility expression like expected value. As background, some properties of RWU are developed.     

Drug use and mental well being among a sample of undergraduate and graduate college students.

Stress related disorders in college students are widespread and largely preventable. Students do not have the preventative skills necessary to manage stress in their lives and, because of the inability to cope, students may turn to alcohol and drugs to alleviate the pressures they are experiencing. The purpose of this study was to describe the association between stress and alcohol and drug use. A total of 772 undergraduate and graduate students from a small, elite, private university were randomly selected from 4000 students to complete two anonymous questionnaires. The Core Alcohol and Drug Survey identified the frequency and consequences of alcohol and drug use, and the General-Well Being Schedule was used to assess subjective well being and mental health status. The results of this study revealed that, for this sample of students, health behaviors such as using drugs recreationally and drinking alcohol played an associative role with general well being. A significant relationship was also found between student participation in intramural or club sports and positive mental well being.     

DISSECTING THE MONTY HALL ANOMALY

We assess competing explanations of irrational behavior in the Monty Hall problem by creating new variants of the problem. Some variants employ a feature that automates the merging of probabilities, thus rendering transparent the probabilistic advantage of the rational choice. That feature also enables systematic variation in informational asymmetry, and in ordering of actions. Data from 77 subjects, each of whom makes 30 binary decisions, indicate that automated merging raises the fraction of rational choices from around 40% to over 80%. Other features examined have much less impact, indicating the importance of a Bayesian updating failure. (JEL C91, D02, D81, D83)