Ethical Numbers: Ethics Training in U.S. Graduate Statistics Programs, 2013–2014

As important members of research teams, statisticians bear an ethical responsibility to analyze, interpret, and report data honestly and objectively. One way of reinforcing ethical responsibilities is through required courses covering a variety of ethics-related topics at the graduate level. We assessed ethics requirements for graduate-level statistics training programs in the United States for the 2013–2014 academic year using the websites of 88 universities, examining 103 biostatistics programs, and 136 statistics degree programs. We categorized programs’ ethics training requirements as required or not required. Thirty-one (35.1%) universities required an ethics course for at least some degree students. Sixty-two (25.5%) degree programs required an ethics course for at least some students. The majority (77.4%) of required courses were worth 0 or 1 credit. Of the 177 programs without an ethics requirement, 19 (10.7%) listed an ethics elective. Although a single ethics course is insufficient for instilling an ethical approach to science, degree programs that model expectations through coursework point to the value of ethics in science. More training programs should prepare statisticians to consider the ethical dimensions of their work through required coursework. Supplementary materials for this article are available online.     

Inequality Assessment by Probabilistic Development Indices

Social Indicators Research - This paper analyses the Human Development Index (HDI) time series from 2010 to 2017. An alternative index is studied, which combines the same components of the HDI by...     

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...     

Robust Designs in Generalized Linear Models: A Quantile Dispersion Graphs Approach

This article studies design selection for generalized linear models (GLMs) using the quantile dispersion graphs (QDGs) approach in the presence of misspecification in the link and/or linear predictor. The uncertainty in the linear predictor is represented by a unknown function and estimated using kriging. For addressing misspecified link functions, a generalized family of link functions is used. Numerical examples are shown to illustrate the proposed methodology.     

The PALS parenting support programme: lessons learned from the evaluation of processes and outcomes

Although there has recently been a rise in parenting support programmes within the UK, only a minority of these programmes have benefited from evaluation of either outcomes or processes. This paper describes the development of the PALS programme (Parents Altogether Lending Support), reporting both on its effectiveness in improving parents' interactions with their children and on the lessons that were learned about embedding such a programme within the local community. Over the 18‐month period of the programme, a total of 17 courses were run, with 75 parents and carers (primarily mothers) participating in the programme overall. Evaluation results indicated that participants enjoyed the course and found it beneficial, particularly in terms of altering their own actions in specific ways that were able to promote better behaviour on the part of their children. Participants also valued the opportunity to share their experiences with other parents. The key lesson identified in regard to the development of parenting programmes concerned the need for the community to feel a sense of ownership for the initiative. Copyright © 2002 John Wiley & Sons, Ltd.     

Book Review: Funding Virtue: Civil Society Aid and Democracy Promotion,Marina Ottaway and Thomas Carothers (eds.), Carnegie Endowment for International Peace,Washington, DC, 2000

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Existence and Nash implementation of efficient sharing rules for a commonly owned technology

Suppose that a group of individuals owns collectively a technology which produces a consumption good by means of a (possibly heterogeneous) input. A sharing rule associates input contributions with a vector of consumptions that are technologically feasible. We show that the set of allocations obtained by any continuous sharing rule contains Pareto efficient allocations. We also present a mechanism that implements in Nash equilibrium the Pareto efficient allocations contained in an arbitrary sharing rule. Received: 29 June 1998/Accepted: 15 November 2000     

REVIEWS

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