Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

A Simulation Study of Some Biasing Parameters for the Ridge Type Estimation of Poisson Regression

This article proposes several estimators for estimating the ridge parameter k based on Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value, and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criteria are very informative because, if several estimators have an equal estimated MSE, then those with low average value and standard deviation of k should be preferred. Based on the simulated results, we may recommend some biasing parameters that may be useful for the practitioners in the field of health, social, and physical sciences.     

Australia and the Global South: Knowledge and the Ambiguities of Place and Identity

Australia was settled as a colony of Britain from the 17th century, and its early history of violent occupation has gradually given way to a relatively peaceful, wealthy, multicultural society. As a post-colonial country, its people share characteristics with those of Britain, but, as a multicultural society, national identity is increasingly influenced by the cultures of many countries, from both the global North and South. In this paper, the question of Australia's placement as a country of the global North or South is explored. Considerations of geography, the economy, political regimes and national identity are the backdrop to an investigation of Australian scholarship and the attitudes of scholars to the inclusion of Australia as a country of the global South.     

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...     

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.     

Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method

Abstract

In general, survival data are time-to-event data, such as time to death, time to appearance of a tumor, or time to recurrence of a disease. Models for survival data have frequently been based on the proportional hazards model, proposed by Cox. The Cox model has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient sampling method of recruiting subjects for survival analysis. We propose using a Moving Extreme Ranked Set Sampling (MERSS) scheme with ranking based on an easy-to-evaluate baseline auxiliary variable known to be associated with survival time. This paper demonstrates that this approach provides a more powerful testing procedure as well as a more efficient estimate of hazard ratio than that based on simple random sampling (SRS). Theoretical derivation and simulation studies are provided. The Iowa 65+ Rural study data are used to illustrate the methods developed in this paper.     

Sex Related Factors in the Perception of Threatening Facial Expressions

This study replicated and extended previously reported sex differences involving both viewer and target in the recognition of threatening facial expressions. Based on the assumption that the evolved cognitive mechanisms mediating anger recognition would have been designed by natural selection to operate quickly in the interests of survival, brief tachistoscopic presentation of stimulus photographs was used. Additionally, in contrast to prior published studies, the statistical methods of signal detection research were used to control for the confounding effects of non-random guessing. The main hypothesis, that anger posed by males would be more accurately perceived than anger posed by females, was supported. A secondary hypothesis, that female-posed anger would be more accurately perceived by women than by men, received partial support. Testosterone levels, measured inferentially in terms of diurnal cycles, failed to show the hypothesized positive relationship to accuracy of anger perception.     

Changing Frameworks in Attitudes Toward Abortion

For more than two decades, legal abortion has been the subject of heated political debate and adversarial social movement activity; however, national polls have shown little change in aggregate levels of support for abortion. This analysis examines how the determinants of abortion attitudes have changed between 1977 and 1996, using data from the General Social Surveys. While in early time periods, whites were more approving of abortion than blacks, that pattern had reversed by the late 1980s. After controlling for other factors, older people are more accepting of abortion throughout the two decades, while gender is generally unrelated to abortion views. Catholic religion weakens slightly as a predictor of abortion attitudes, while religious fundamentalism and political liberalism increase in explanatory power. The associations between attitudinal correlates and abortion approval also change over this time period. Religiosity becomes a less powerful predictor of abortion attitudes, while respondents' attitude toward sexual freedom and belief in the sanctity of human life increase in their predictive power. Support for gender inequality remains a weak but stable predictor of abortion attitudes. This pattern of results suggests that the public is influenced more by the pro-life framework of viewing abortion than by the pro-choice perspective.