Novel biotechnologies for eradicating wasps: seeking Māori studies students’ perspectives with Q method

Aligned with the New Zealand government’s ‘Predator-Free 2050’ target for Aotearoa New Zealand, National Science Challenge: Our Biological Heritage supports research into five distinct ‘novel biotechnological controls’ of exotic wasps. A framing question within this project is which controls are considered ‘socially acceptable’ and thus suitable for further development to control and potentially eradicate introduced wasps? How can the public answer this question without first engaging with complex technologies? Can they develop and express an informed view that still reflects their ‘gut’ reactions and unique positions? To model and explore the views of an ‘informed public’, university students in Māori studies engaged in reflection, writing and mapping activities; choice and ranking exercises; Q Method; and focus group interviews. Amongst the interviewees, Q Method analysis distinguished three ‘factors’, describing unique viewpoints: those who see the potential of biotechnologies, those who are in doubt about them and those in a position of trust in scientists. Overall, the group see potential in new biotechnologies for wasps but are wary of political, economic and social decision-making mechanisms.     

A Bayesian approach for parameter estimation in multi-stage models

Multi-stage time evolving models are common statistical models for biological systems, especially insect populations. In stage-duration distribution models, parameter estimation for the models use the Laplace transform method. This method involves assumptions such as known constant shapes, known constant rates or the same overall hazard rate for all stages. These assumptions are strong and restrictive. The main aim of this paper is to weaken these assumptions by using a Bayesian approach. In particular, a Metropolis-Hastings algorithm based on deterministic transformations is used to estimate parameters. We will use two models, one which has no hazard rates, and the other has stage-wise constant hazard rates. These methods are validated in simulation studies followed by a case study of cattle parasites. The results show that the proposed methods are able to estimate the parameters comparably well, as opposed to using the Laplace transform methods.     

On the asymptotic non‐equivalence of efficient‐GMM and MEL estimators in models with missing data

The generalized method of moments (GMM) and empirical likelihood (EL) are popular methods for combining sample and auxiliary information. These methods are used in very diverse fields of research, where competing theories often suggest variables satisfying different moment conditions. Results in the literature have shown that the efficient‐GMM (GMM_E) and maximum empirical likelihood (MEL) estimators have the same asymptotic distribution to order n^?1/2 and that both estimators are asymptotically semiparametric efficient. In this paper, we demonstrate that when data are missing at random from the sample, the utilization of some well‐known missing‐data handling approaches proposed in the literature can yield GMM_E and MEL estimators with nonidentical properties; in particular, it is shown that the GMM_E estimator is semiparametric efficient under all the missing‐data handling approaches considered but that the MEL estimator is not always efficient. A thorough examination of the reason for the nonequivalence of the two estimators is presented. A particularly strong feature of our analysis is that we do not assume smoothness in the underlying moment conditions. Our results are thus relevant to situations involving nonsmooth estimating functions, including quantile and rank regressions, robust estimation, the estimation of receiver operating characteristic (ROC) curves, and so on.     

Gay officers in their midst: heterosexual police employees' anticipation of the consequences for coworkers who come out

While fear among gay men and lesbians about being out in a masculinist environment is not surprising, this article examines what heterosexuals expect will happen when gay men and lesbians come out. We draw on a unique dataset from a police department in the southwest United States to examine the consequences anticipated by heterosexual police department employees if a gay or lesbian officer's sexual orientation became known in the workplace. We test four main sets of factors: individual-level demographic characteristics and religious background; homophobia; organizational tolerance for discrimination; and intergroup contact theory to explain how heterosexuals expect gay and lesbian coworkers to be treated. Using ordinary least squares regression, we find that characteristics of workplaces, measured by tolerance of discrimination, as well as contact with gay men and lesbians on the job are more significant predictors of anticipated outcomes than are individual-level traits and homophobic attitudes. We conclude by discussing the policy implications of our research.     

Two-stage k-sample designs for the ordered alternative problem

In preclinical studies and clinical dose-ranging trials, the Jonckheere-Terpstra test is widely used in the assessment of dose-response relationships. Hewett and Spurrier (1979) presented a two-stage analog of the test in the context of large sample sizes. In this paper, we propose an exact test based on Simon's minimax and optimal design criteria originally used in one-arm phase II designs based on binary endpoints. The convergence rate of the joint distribution of the first and second stage test statistics to the limiting distribution is studied, and design parameters are provided for a variety of assumed alternatives. The behavior of the test is also examined in the presence of ties, and the proposed designs are illustrated through application in the planning of a hypercholesterolemia clinical trial. The minimax and optimal two-stage procedures are shown to be preferable as compared with the one-stage procedure because of the associated reduction in expected sample size for given error constraints.     

Additional results for 'Sequential design approaches for bioequivalence studies with crossover designs'

In 2008, this group published a paper on approaches for two‐stage crossover bioequivalence (BE) studies that allowed for the reestimation of the second‐stage sample size based on the variance estimated from the first‐stage results. The sequential methods considered used an assumed GMR of 0.95 as part of the method for determining power and sample size. This note adds results for an assumed GMR = 0.90. Two of the methods recommended for GMR = 0.95 in the earlier paper have some unacceptable increases in Type I error rate when the GMR is changed to 0.90. If a sponsor wants to assume 0.90 for the GMR, Method D is recommended. Copyright © 2011 John Wiley & Sons, Ltd.     

Likelihood‐based inferences about the mean area under a longitudinal curve in the presence of observations subject to limits of detection

Comparison of groups in longitudinal studies is often conducted using the area under the outcome versus time curve. However, outcomes may be subject to censoring due to a limit of detection and specific methods that take informative missingness into account need to be applied. In this article, we present a unified model‐based method that accounts for both the within‐subject variability in the estimation of the area under the curve as well as the missingness mechanism in the event of censoring. Simulation results demonstrate that our proposed method has a significant advantage over traditionally implemented methods with regards to its inferential properties. A working example from an AIDS study is presented to demonstrate the applicability of our approach. Copyright © 2015 John Wiley & Sons, Ltd.     

How and Why Do Family and Systemic Therapies Work?

My reviews of the evidence base for family therapy conducted over the past 15 years have been guided by four key questions. Does systemic therapy work? What sorts of systemic therapy work for specific problems? What processes occur in effective systemic therapy? Is systemic therapy cost‐effective? In this paper answers to these questions are given. Systemic interventions are effective for about two out of three cases. Specific models of effective systemic therapy have been developed for most common mental health problems. There are many processes shared by evidence‐based models of practice that can be incorporated into the routine practice of research‐informed family therapy. Systemic therapy is cost‐effective and in many cases leads to medical cost‐offsets. Available evidence indicates that family therapy can make a very significant contribution to alleviating suffering and making the world a better place to be.