An Additive–Multiplicative Restricted Mean Residual Life Model

The mean residual life measures the expected remaining life of a subject who has survived up to a particular time. When survival time distribution is highly skewed or heavy tailed, the restricted mean residual life must be considered. In this paper, we propose an additive–multiplicative restricted mean residual life model to study the association between the restricted mean residual life function and potential regression covariates in the presence of right censoring. This model extends the proportional mean residual life model using an additive model as its covariate dependent baseline. For the suggested model, some covariate effects are allowed to be time‐varying. To estimate the model parameters, martingale estimating equations are developed, and the large sample properties of the resulting estimators are established. In addition, to assess the adequacy of the model, we investigate a goodness of fit test that is asymptotically justified. The proposed methodology is evaluated via simulation studies and further applied to a kidney cancer data set collected from a clinical trial.     

Manual flying skills under the influence of performance shaping factors

This paper describes an experimental study investigating pilots' manual flying skills. In today's line oriented flight training, basic flying skills are neglected frequently. So, the study examines the manual flying skills of commercial airline pilots under the influence of several performance shaping factors like training, practice or fatigue in a landing scenario. The landing phase shows a disproportionate high percentage of aircraft accidents and it is typically flown by hand. The study is to be undertaken with randomly selected pilots in a full motion flight simulator to ensure a high validity of the results.     

DOES THE PUBLIC SECTOR IMPLODE FROM BAUMOL'S COST DISEASE?

The root of the Baumol cost disease is higher productivity increases for manufactured goods than for services. The implied increase in relative costs of service production is widely claimed to have devastating implications for the public sector as a provider of tax‐financed services such as health, education, and care. To match the increasing costs it appears inevitable that tax rates would be ever increasing. It is shown that this inference does not follow under standard assumptions when accounting explicitly for service provision from both the private and public sectors. Strikingly under assumptions often made in the literature, the welfare maximizing tax rate for a utilitarian policy maker would remain constant despite the Baumol cost disease, and by implication the share of public employment in total employment will remain constant. (JEL H5, H11, O41)     

Engaging with Comparative Risk Appraisals: Public Views on Policy Priorities for Environmental Risk Governance

Communicating the rationale for allocating resources to manage policy priorities and their risks is challenging. Here, we demonstrate that environmental risks have diverse attributes and locales in their effects that may drive disproportionate responses among citizens. When 2,065 survey participants deployed summary information and their own understanding to assess 12 policy‐level environmental risks singularly, their assessment differed from a prior expert assessment. However, participants provided rankings similar to those of experts when these same 12 risks were considered as a group, allowing comparison between the different risks. Following this, when individuals were shown the prior expert assessment of this portfolio, they expressed a moderate level of confidence with the combined expert analysis. These are important findings for the comprehension of policy risks that may be subject to augmentation by climate change, their representation alongside other threats within national risk assessments, and interpretations of agency for public risk management by citizens and others.     

Cox regression with missing covariate data using a modified partial likelihood method

Missing covariate values is a common problem in survival analysis. In this paper we propose a novel method for the Cox regression model that is close to maximum likelihood but avoids the use of the EM-algorithm. It exploits that the observed hazard function is multiplicative in the baseline hazard function with the idea being to profile out this function before carrying out the estimation of the parameter of interest. In this step one uses a Breslow type estimator to estimate the cumulative baseline hazard function. We focus on the situation where the observed covariates are categorical which allows us to calculate estimators without having to assume anything about the distribution of the covariates. We show that the proposed estimator is consistent and asymptotically normal, and derive a consistent estimator of the variance–covariance matrix that does not involve any choice of a perturbation parameter. Moderate sample size performance of the estimators is investigated via simulation and by application to a real data example.     

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.     

Beratungsforschung mit,für oder ohne die Praxis?

This article deals with the extent to which consulting research and consulting practice are pulling in the same direction or whether the gap between them still seems insurmountable. Therefore we examine the literature on consulting research, report what kind of research coaching practitioners would consider beneficial and introduce first findings from an empirical survey in which coaching practitioners were asked about their motivation for—or against—taking part in coaching research.     

Wie undicht ist die Pipeline? Wissenschaftskarrieren von promovierten Frauen

Which mechanisms lead to the fact, that the proportion of women in the academic career ladder is the smaller the further up the qualification and career to full professorship gets? This phenomenon, known as the ??leaky pipeline??, is analysed with a unique retrospective dataset of PhDs who graduated between 1996 and 2002 at universities in the German speaking part of Switzerland. Results show women have a lower scientific productivity and smaller academic networks than men. Moreover, they suffer from structural barriers in the scientific system. However, women stay in the sector of higher education more often than men and habilitate as often as their male colleagues. Transition rate models show no gender differences in the chance of a successful academic career. Because meanwhile women start to study as often as men, today??s picture of the leaky pipeline could be a result of gender inequalities of the past. Future research should examine the role of affirmative action for women in academia and how results from scientific careers can be transferred into the private labour market.     

Estimation of Causal Odds of Concordance using the Aalen Additive Model

A simple summary of a treatment effect is attractive, which is part of the explanation of the success of the Cox model when analysing time‐to‐event data since the relative risk measure is such a convenient summary measure. In practice, however, the Cox model may fail to give a reasonable fit, very often because of time‐changing treatment effect. The Aalen additive hazards model may be a good alternative as time‐changing effects are easily modelled within this model, but results are then evidently more complicated to communicate. In such situations, the odds of concordance measure (OC) is a convenient way of communicating results, and recently Martinussen & Pipper (2012) showed how a variant of the OC measure may be estimated based on the Aalen additive hazards model. In this study, we propose an estimator that should be preferred in observational studies as it always estimates the causal effect on the chosen scale, only assuming that there are no un‐measured confounders. The resulting estimator is shown to be consistent and asymptotically normal, and an estimator of its limiting variance is provided. Two real applications are provided.     

Organizational climate and burnout in a New Zealand social service agency

Abstract

A two-phase study was conducted on the relationship between organizational climate variables and burnout among personnel in a multifunction community service agency. Initial interviews with a small pilot sample identified major sources of stress, which were then incorporated into a second-phase questionnaire to all staff. Multiple regression analyses illustrated that perceived interactions between head office administrators and sections of the agency contributed significantly to emotional exhaustion, whereas perceptions of within-section interactions and involvement in decision-making had a positive impact on personal accomplishment. Perceived communication levels, however, were negatively related to personal accomplishment. The findings suggest the importance of organizational variables and highlight strategies for burnout reduction and effective stress management in human service organizations.