Fitting Weibull duration models with random effects

Duration time models often should include correlated failure times, due to clustered data. These random effects hierarchical models sometimes are called frailty models when used for survival analyses. The data analyzed here involve such correlations because patient level outcomes (the times until graft failure following kidney transplantation) are observed, but patients are clustered in different transplant centers. We describe fitting such models by combining two kinds of software, one for parametric survival regression models, and the other for doing Poisson regression in a hierarchical setting. The latter is implemented by using PRIMM (Poisson Regression and Interactive Multilevel Modeling) methods and software (Christiansen & Morris, 1994a). An illustrative example for profiling data is included withk=11 kidney transplant centers andN=412 patients.     

Ths State of Welfare. Gilbert Steiner. The Brookings Institution,Washington, D. C., 1971. 356 Pages, $7.50 Hardbound

A questionnaire was developed to elicit data concerning processes and criteria used in graduate programs of social work for retention, promotion, and granting tenure to faculty members. Eighty percent of the 85 graduate programs of social work within the United States and Canada responded to the questionnaire. The results of that study are reported in this paper. Also examined was the source or sanction of the decision—either specific to the program or applied in accordance with a broader academic base, that is, graduate school or university procedures.     

American Public Opinion on Immigration: Nativist,Polarized, or Ambivalent?

For Dauvergne (2016), one consequence of the “end of settler societies” is nativism, or what she calls “mean-spirited politics”: anti-immigrant, anti-Muslim, anti-Multiculturalism. This accords with the prevailing tone of public opinion literature on the subject, which links anti-immigrant hostility in settler societies to influxes of diversity and associated racial threat. In this essay, we determine just how closely this stylized vision of anxiety-fuelled nativism resembles the true state of mass opinion about immigration. Using a variety of surveys fielded in recent years, we show that Americans: 1) hold generally positive views about immigration, though with a substantial dose of ambivalence about its consequences; 2) are not especially consistent in their policy attitudes over time; 3) express policy attitudes that readily depart from their underlying predispositions, and; 4) have only become more pro-immigrant in recent years, and whatever partisan polarization exists on the issue stems from the fact that Republicans are becoming more positive at a slightly slower pace than Democrats. All of this suggests that, while there is a hard core of ethnocentrism and "mean-spiritedness" in the U.S., the prevailing tone is much less negative than the standard portrayal assumes.     

International work experience and compensation: Is more always better for CFOs?

The CFO is increasingly considered the second most important executive in the firm after the CEO. Still, little is known about the factors that determine CFOs' compensation. Recently, it has often been claimed that, in MNCs, CFOs should have international work experience. But is a CFO's international work experience also reflected in his or her compensation? We combine human capital and social capital perspectives to account for both the upside and the downside of international work experience. We suggest that working abroad provides CFOs with valuable knowledge and skills which increase compensation; however, staying abroad for too long has an adverse effect due to losses in social network ties. We thus propose an inverted U-shaped relationship between CFOs' international work experience and their compensation. Furthermore, we suggest that this relationship is contingent on the characteristics of the CEO. In testing our hypotheses on a sample of the largest MNCs in Europe, we find support for the proposed relationships. Our study contributes to the literature on top management characteristics and executive compensation, specifically by providing a comprehensive understanding of how and when international work experience pays off for CFOs.     

News and Comment

Holocaust education in the United States began as a grassroots movement during the 1970s. Today, more than 30 states mandate the teaching of the Holocaust; however, far less attention is given in schools to other 20th-century instances of genocide. Totten has suggested that by neglecting “other” genocides (e.g., Darfur, Rwanda, and Cambodia), these events may not be perceived as significant (when compared to the Holocaust), and moreover, students may fail to realize that genocide has occurred multiple times since 1945 and thus no longer a threat today. Given the implications surrounding Totten’s assertion and the global nature of genocide and its reach, we aim to provide social studies teachers and teacher educators with a series of accessible suggestions for incorporating “other” genocides into their practice—suggestions that are aligned and situated within Hanvey’s seminal conceptual frame for global education.     

Bayesian Random Segmentation Models to Identify Shared Copy Number Aberrations for Array CGH Data

Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. We propose a hierarchical Bayesian random segmentation approach for modeling aCGH data that utilizes information across arrays from a common population to yield segments of shared copy number changes. These changes characterize the underlying population and allow us to compare different population aCGH profiles to assess which regions of the genome have differential alterations. Our method, referred to as BDSAcgh (Bayesian Detection of Shared Aberrations in aCGH), is based on a unified Bayesian hierarchical model that allows us to obtain probabilities of alteration states as well as probabilities of differential alteration that correspond to local false discovery rates. We evaluate the operating characteristics of our method via simulations and an application using a lung cancer aCGH data set.     

Stochasticity in Physiologically Based Kinetics Models: Implications for Cancer Risk Assessment

In case of low-dose exposure to a substance, its concentration in cells is likely to be stochastic. Assessing the consequences of this stochasticity in toxicological risk assessment requires the coupling of macroscopic dynamics models describing whole-body kinetics with microscopic tools designed to simulate stochasticity. In this article, we propose an approach to approximate stochastic cell concentration of butadiene in the cells of diverse organs. We adapted the dynamics equations of a physiologically based pharmacokinetic (PBPK) model and used a stochastic simulator for the system of equations that we derived. We then coupled kinetics simulations with a deterministic hockey stick model of carcinogenicity. Stochasticity induced substantial modifications relative to dose-response curve, compared with the deterministic situation. In particular, there was nonlinearity in the response and the stochastic apparent threshold was lower than the deterministic one. The approach that we developed could easily be extended to other biological studies to assess the influence of stochasticity at macroscopic scale for compound dynamics at the cell level.