Synthetic data method to incorporate external information into a current study

We consider the situation where there is a known regression model that can be used to predict an outcome, Y, from a set of predictor variables X . A new variable B is expected to enhance the prediction of Y. A dataset of size n containing Y, X and B is available, and the challenge is to build an improved model for Y| X ,B that uses both the available individual level data and some summary information obtained from the known model for Y| X . We propose a synthetic data approach, which consists of creating m additional synthetic data observations, and then analyzing the combined dataset of size n + m to estimate the parameters of the Y| X ,B model. This combined dataset of size n + m now has missing values of B for m of the observations, and is analyzed using methods that can handle missing data (e.g., multiple imputation). We present simulation studies and illustrate the method using data from the Prostate Cancer Prevention Trial. Though the synthetic data method is applicable to a general regression context, to provide some justification, we show in two special cases that the asymptotic variances of the parameter estimates in the Y| X ,B model are identical to those from an alternative constrained maximum likelihood estimation approach. This correspondence in special cases and the method's broad applicability makes it appealing for use across diverse scenarios. The Canadian Journal of Statistics 47: 580–603; 2019 © 2019 Statistical Society of Canada     

A Poisson-multinomial mixture approach to grouped and right-censored counts

Although count data are often collected in social, psychological, and epidemiological surveys in grouped and right-censored categories, there is a lack of statistical methods simultaneously taking both grouping and right-censoring into account. In this research, we propose a new generalized Poisson-multinomial mixture approach to model grouped and right-censored (GRC) count data. Based on a mixed Poisson-multinomial process for conceptualizing grouped and right-censored count data, we prove that the new maximum-likelihood estimator (MLE-GRC) is consistent and asymptotically normally distributed for both Poisson and zero-inflated Poisson models. The use of the MLE-GRC, implemented in an R function, is illustrated by both statistical simulation and empirical examples. This research provides a tool for epidemiologists to estimate incidence from grouped and right-censored count data and lays a foundation for regression analyses of such data structure.     

Resilience of Cyber Systems with Over‐ and Underregulation

Recent cyber attacks provide evidence of increased threats to our critical systems and infrastructure. A common reaction to a new threat is to harden the system by adding new rules and regulations. As federal and state governments request new procedures to follow, each of their organizations implements their own cyber defense strategies. This unintentionally increases time and effort that employees spend on training and policy implementation and decreases the time and latitude to perform critical job functions, thus raising overall levels of stress. People's performance under stress, coupled with an overabundance of information, results in even more vulnerabilities for adversaries to exploit. In this article, we embed a simple regulatory model that accounts for cybersecurity human factors and an organization's regulatory environment in a model of a corporate cyber network under attack. The resulting model demonstrates the effect of under‐ and overregulation on an organization's resilience with respect to insider threats. Currently, there is a tendency to use ad‐hoc approaches to account for human factors rather than to incorporate them into cyber resilience modeling. It is clear that using a systematic approach utilizing behavioral science, which already exists in cyber resilience assessment, would provide a more holistic view for decisionmakers.     

Immigration in the 2008 Virginia presidential election: A cultural issue remains puissant despite an economic crisis

In 2006 and 2007, many analysts expected that immigration would be one of the top domestic issues in the 2008 campaign. However, in the 2008 presidential general election, immigration issues were never a major topic between candidates John McCain and Barack Obama. This was partially because McCain has more moderate views toward immigration reform than the passionate anti-immigration faction of the Republican Party. Prior research suggests that an issue in a presidential campaign can remain influential even when the media and campaigns are not discussing or addressing the issue, even when the candidates or parties do not differ greatly on the issue. In a survey of Virginia residents conducted just before the November election, immigration attitudes were a differential factor between McCain and Obama.     

Skin color,sex, and educational attainment in the post-civil rights era

We assess the relationship between skin color and educational attainment for native-born non-Hispanic Black and White men and women, using data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study. CARDIA is a medical cohort study with twenty years of social background data and a continuous measure of skin color, recorded as the percent of light reflected off skin. For Black men and women, we find a one-standard-deviation increase in skin lightness to be associated with a quarter-year increase in educational attainment. For White women, we find an association approximately equal in magnitude to that found for Black respondents, and the pattern of significance across educational transitions suggests that skin color for White women is not simply a proxy for family background. For White men, any relationship between skin color and attainment is not robust and, analyses suggest, might primarily reflect differences in family background. Findings suggest that discrimination on the basis of skin color may be less specific to race than previously thought.     

Comparison of conflict of interest policies and reported practices in academic medical centers in the United States

The authors reviewed the conflict of interest policies of 9 academic medical centers in the United States and interviewed members of the Institutional Review Boards (IRBs) and Conflict of Interest Committees (COICs) at those institutions. They found that many institutions used processes for reporting and managing conflicts of interest that were more decentralized than the processes described in their policies. Also, most institutions had no clear and comprehensive policy to guide investigators regarding disclosure of conflicts of interest to potential research participants. Considerable differences in understanding of conflict of interest policies were observed between IRB and COIC officials.     

Editorial

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Ethics in population-based genetic research

Population-based genetic research, including genetic epidemiology, shows tremendous potential to elucidate the role of genes as causal factors in complex and common human diseases. Like all research with human subjects, full realization of these benefits requires careful attention to its ethical conduct, establishing an appropriate balance between individual protections and the advancement of scientific and medical knowledge. This article reviews the growing literature on genetics research and ethics to describe some of the fundamental ethical issues in population-based genetics research, including research design, recruitment and informed consent, and dealing with research results. Its focus is on areas where consensus is forming and where future work is needed.