Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

The Impact of Neighboring on Changes in Sense of Community Over Time: A Latent Transition Analysis

Sense of community (SOC) is associated with the quality of community life and the building of social capital. While its linkage to informal social behavior, such as neighboring, is inherent in discussions regarding theory, empirical evidence remains scarce. Moreover, the degree to which neighboring behavior influences SOC over time is largely unknown. Using a latent transition analysis, the effect of neighboring on SOC was investigated over a 5-year span from 2006 to 2011 among a sample of adults (n?=?165) in Arizona. Initially, a latent class analysis identified two SOC subgroups: Low SOC and High SOC. The likelihood of shifts in SOC class membership over 5 years was generally stable, with most individuals staying in the same group (82.3% Low SOC; 92.4% High SOC). Neighboring behavior and socio-demographic covariates impacted the likelihood that individuals changed classes, with 25.3% of Low SOC individuals transitioning to High SOC in 2011 and 55.4% of High SOC individuals moving to Low SOC in 2011. Specifically, having an income greater than $60,000 and visiting with neighbors lessened the likelihood of being in the Low SOC class in 2006; and length of residence and exchanging favors with neighbors lessened the likelihood of being in the Low SOC class in 2011. These findings have implications for both community design and community development practice. Design and development interventions that promote greater social interaction may help build and sustain SOC over time.

     

Foreign-born and native-born migration in the U.S.: evidence from linked IRS administrative and census survey records

Journal of Population Research - This paper details efforts to link administrative records from the Internal Revenue Service (IRS) to American Community Survey (ACS) and 2010 Census microdata for...     

A class of symmetric bivariate uniform distributions

A class of symmetric bivariate uniform distributions is proposed for use in statistical modeling. The distributions may be constructed to be absolutely continuous with correlations as close to±1 as desired. Expressions for the correlations, regressions and copulas are found. An extension to three dimensions is proposed.     

Still-births among the offspring of male radiation workers at the Sellafield nuclear reprocessing plant: detailed results and statistical aspects

Summary. This study investigates whether there was evidence of increasing risk of still-birth with increasing paternal exposure to ionizing radiation received during employment at the Sellafield nuclear installation before the child was conceived. A significant positive association is found between the total paternal preconceptional exposure to external ionizing radiation and the risk of still-birth (after adjustment for year of birth, social class, birth order and paternal age, odds ratio at 100 mSv 1.24 (95% confidence interval 1.04–1.45)). A summary of the principal scientific findings of this study has been published in the Lancet . This paper describes in detail the statistical methods that were used in the investigation and presents the results in full.     

'It is a horrible term for someone': service user and provider perspectives on 'personality disorder'

This paper presents findings from a study exploring the views of people with personality disorder diagnoses and various professionals working with them. After outlining the policy context and the study's conceptual framework, the aims and methods are described. Interviews were conducted with 12 service providers and 10 users. The main findings are then discussed, including user and provider perspectives on the meaning of 'personality disorder' and the strategies and support people use to address their difficulties. Finally, the theoretical implications of the findings are discussed.