The time‐dependent “cure‐death” model investigating two equally important endpoints simultaneously in trials treating high‐risk patients with resistant pathogens

A variety of primary endpoints are used in clinical trials treating patients with severe infectious diseases, and existing guidelines do not provide a consistent recommendation. We propose to study simultaneously two primary endpoints, cure and death, in a comprehensive multistate cure‐death model as starting point for a treatment comparison. This technique enables us to study the temporal dynamic of the patient‐relevant probability to be cured and alive. We describe and compare traditional and innovative methods suitable for a treatment comparison based on this model. Traditional analyses using risk differences focus on one prespecified timepoint only. A restricted logrank‐based test of treatment effect is sensitive to ordered categories of responses and integrates information on duration of response. The pseudo‐value regression provides a direct regression model for examination of treatment effect via difference in transition probabilities. Applied to a topical real data example and simulation scenarios, we demonstrate advantages and limitations and provide an insight into how these methods can handle different kinds of treatment imbalances. The cure‐death model provides a suitable framework to gain a better understanding of how a new treatment influences the time‐dynamic cure and death process. This might help the future planning of randomised clinical trials, sample size calculations, and data analyses.     

Academic economists behaving badly? A survey on three areas of unethical behavior

This article measures the degree to which academic economists have engaged in unethical behavior and the degree to which academic economists believe the profession as a whole engages in unethical behavior. Three main types of unethical behavior are examined: (1) falsification of research; (2) expropriation of graduate student research or including an undeserving co-author on a research paper; and (3) exchange of grades for gifts, money, or sex. Using a unique data set gathered at the 1998 American Economic Association (AEA) meetings, we find that there is a significant amount of misconduct, particularly in the second category.     

How Sunday, price, and social norms influence donation behaviour

We describe a natural field experiment investigating donation behaviour. The setting was an art gallery where donations could be deposited into a transparent box in the foyer. Two aspects of the donation environment were manipulated: signs on the donation box and the initial contents of the box. We used three sign treatments: a control with no sign, a sign that thanked donors, and a sign that indicated donations would be matched. We used two initial contents treatments: one with relatively little money ($50) and one with four times as much. The average donation per donor was significantly larger in the $200 treatments but this was offset by a decrease in the propensity to donate. In the matching treatments donations were significantly larger both at the per donor and per visitor level. A control variable turned out to have the largest influence on donation behaviour: the day of the week. The average donation per visitor was 51% higher on Sundays, when compared to every other day of the week.     

A Note on the Large Sample Properties of Estimators Based on Generalized Linear Models for Correlated Pseudo‐observations

Pseudo‐values have proven very useful in censored data analysis in complex settings such as multi‐state models. It was originally suggested by Andersen et al., Biometrika, 90, 2003, 335 who also suggested to estimate standard errors using classical generalized estimating equation results. These results were studied more formally in Graw et al., Lifetime Data Anal., 15, 2009, 241 that derived some key results based on a second‐order von Mises expansion. However, results concerning large sample properties of estimates based on regression models for pseudo‐values still seem unclear. In this paper, we study these large sample properties in the simple setting of survival probabilities and show that the estimating function can be written as a U‐statistic of second order giving rise to an additional term that does not vanish asymptotically. We further show that previously advocated standard error estimates will typically be too large, although in many practical applications the difference will be of minor importance. We show how to estimate correctly the variability of the estimator. This is further studied in some simulation studies.     

Validation of Nonparametric Two-sample Bootstrap in ROC Analysis on Large Datasets

The nonparametric two-sample bootstrap is applied to computing uncertainties of measures in receiver operating characteristic (ROC) analysis on large datasets in areas such as biometrics, speaker recognition, etc. when the analytical method cannot be used. Its validation was studied by computing the standard errors of the area under ROC curve using the well-established analytical Mann–Whitney statistic method and also using the bootstrap. The analytical result is unique. The bootstrap results are expressed as a probability distribution due to its stochastic nature. The comparisons were carried out using relative errors and hypothesis testing. These match very well. This validation provides a sound foundation for such computations.     

The Local Power of the CADF and CIPS Panel Unit Root Tests

Very little is known about the local power of second generation panel unit root tests that are robust to cross-section dependence. This article derives the local asymptotic power functions of the cross-section argumented Dickey–Fuller Cross-section Augmented Dickey-Fuller (CADF) and CIPS tests of Pesaran (2007), which are among the most popular tests around.     

The Transitional Discharge Model: comparing implementation in Canada and Scotland

Effective discharge planning is needed to facilitate clients' transition from psychiatric hospital wards to community care. Previous studies have shown that client outcomes can be improved by using a Transitional Discharge Model (TDM) that includes peer support and an extension of inpatient-practitioner relationships that are introduced prior to discharge. However, countries vary in many ways that may affect implementation of the model. This article describes some of the similarities and differences related to introducing transitional discharge in two countries: Canada and Scotland. It is important to elucidate facilitators and challenges in implementing the TDM to identify and disseminate strategies to aid implementation. Implications for future implementation of the model are also discussed.