Assessment of modeling longitudinal binary data based on graphical methods

Longitudinal categorical data are commonly applied in a variety of fields and are frequently analyzed by generalized estimating equation (GEE) method. Prior to making further inference based on the GEE model, the assessment of model fit is crucial. Graphical techniques have long been in widespread use for assessing the model adequacy. We develop alternative graphical approaches utilizing plots of marginal model-checking condition and local mean deviance to assess the GEE model with logit link for longitudinal binary responses. The applications of the proposed procedures are illustrated through two longitudinal binary datasets.     

利用伪随机信号系统辨识钻柱系统

用白噪声信号作为输入信号对钻柱系统脉冲响应进行辨识。研究了伪随机信号的特征及伪随机信号产生的方法,得出了用伪随机信号代替白噪声信号辨识钻柱系统脉冲响应的结论。结合输入信号和输出信号,利用钻柱系统的脉冲响应,讨论了钻柱的临界转速、钻柱共振、钻柱与井壁之间的相互作用、所钻地层岩性等钻井工程问题。     

Dose‐Response Models Incorporating Aerosol Size Dependency for Francisella tularensis

The effect of bioaerosol size was incorporated into predictive dose‐response models for the effects of inhaled aerosols of Francisella tularensis (the causative agent of tularemia) on rhesus monkeys and guinea pigs with bioaerosol diameters ranging between 1.0 and 24 μm. Aerosol‐size‐dependent models were formulated as modification of the exponential and β‐Poisson dose‐response models and model parameters were estimated using maximum likelihood methods and multiple data sets of quantal dose‐response data for which aerosol sizes of inhaled doses were known. Analysis of F. tularensis dose‐response data was best fit by an exponential dose‐response model with a power function including the particle diameter size substituting for the rate parameter k scaling the applied dose. There were differences in the pathogen's aerosol‐size‐dependence equation and models that better represent the observed dose‐response results than the estimate derived from applying the model developed by the International Commission on Radiological Protection (ICRP, 1994) that relies on differential regional lung deposition for human particle exposure.     

Treatment Choice With Trial Data: Statistical Decision Theory Should Supplant Hypothesis Testing

Abstract

A central objective of empirical research on treatment response is to inform treatment choice. Unfortunately, researchers commonly use concepts of statistical inference whose foundations are distant from the problem of treatment choice. It has been particularly common to use hypothesis tests to compare treatments. Wald’s development of statistical decision theory provides a coherent frequentist framework for use of sample data on treatment response to make treatment decisions. A body of recent research applies statistical decision theory to characterize uniformly satisfactory treatment choices, in the sense of maximum loss relative to optimal decisions (also known as maximum regret). This article describes the basic ideas and findings, which provide an appealing practical alternative to use of hypothesis tests. For simplicity, the article focuses on medical treatment with evidence from classical randomized clinical trials. The ideas apply generally, encompassing use of observational data and treatment choice in nonmedical contexts.     

Bittersweet and Paradoxical

The American Red Cross is the most active nonprofit organization involved in disaster planning and response in the United States. The organization deployed nearly 50,000 volunteers to provide essential support to victims of some 125,000 domestic disasters, including home fires, hurricanes, wildfires, and floods, in a recent two‐year period. This study asks how American Red Cross disaster response volunteer experiences function to cultivate satisfaction and, at the other end of the spectrum, the kind of dissatisfaction that leads people to quit; it pays particular attention to ways in which volunteer management shapes dissatisfaction and fatigue because of implications for volunteer retention. Paradoxically, the Red Cross facilitates the highly satisfying act of helping victims, but volunteers feel dissatisfied when management practices get in the way of helping. The study suggests voluntary organizations that rely on skilled, long‐term volunteers to deliver services should evaluate and strengthen their communication strategies, recognition practices, and support systems for volunteers in distress.     

Humanitarian response and stress in Kenya: gendered problems and their implications

ABSTRACT

Stress-related conditions such as burnout and post-traumatic stress disorder are a growing concern in the humanitarian sector. Aid workers themselves report not only that mental health problems are common, but that the support they receive from their employers is insufficient. Problematically, the experience of the international aid worker – particularly those who are white and from the global North – is often foregrounded in explaining what constitutes stress and related mental health problems. This indicates a wider problem of what is required of ‘the perfect humanitarian’ – a personality that is gendered and racialised – and how this influences the different experiences and treatment of national and international staff from aid agencies. This article explores the organisational culture and working conditions of humanitarian settings and their impact on the mental health and well-being of staff. It argues that there is a structural dimension to stress that is less to do with external security threats and more to do with the specific infrastructure, policies, and practices of humanitarian operations, with implications for aid workers which cut across dimensions of race, gender, and nationality.     

A pool-adjacent-violators-algorithm approach to detect infinite parameter estimates in one-regressor dose–response models with asymptotes

Binary response models are often applied in dose–response settings where the number of dose levels is limited. Commonly, one can find cases where the maximum likelihood estimation process for these models produces infinite values for at least one of the parameters, often corresponding to the ‘separated data’ issue. Algorithms for detecting such data have been proposed, but are usually incorporated directly into in the parameter estimation. Additionally, they do not consider the use of asymptotes in the model formulation. In order to study this phenomenon in greater detail, we define the class of specifiably degenerate functions where this can occur (including the popular logistic and Weibull models) that allows for asymptotes in the dose–response specification. We demonstrate for this class that the well-known pool-adjacent-violators algorithm can efficiently pre-screen for non-estimable data. A simulation study demonstrates the frequency with which this problem can occur for various response models and conditions.     

Effects of attributed responsibility and response strategies on organizational reputation: A meta-analysis of situational crisis communication theory research

Scholars utilizing situational crisis communication theory (SCCT) mainly examine how attributed responsibility affects organizational reputation and how response strategies matched with the amount of attributed responsibility protect reputation. The findings on these 2 important questions have been mixed. A meta-analysis of 35 investigations from 24 studies published between January 1990 and March 2015 was conducted to explain the mixed findings and reveal average correlations. Attributed responsibility was strongly associated with reputation at –.54, and response strategies were only weakly associated with reputation at .23. Equally important, crisis vignette choice moderated the responsibility-reputation association. Crisis clusters, reputation measurements, sample choice, and crisis vignette choice moderated the match-reputation association. Theoretical, methodological, and practical implications were discussed.     

Pseudo-Bayes and pseudo-empirical Bayes estimators in randomized response sampling

In this article, new pseudo-Bayes and pseudo-empirical Bayes estimators for estimating the proportion of a potentially sensitive attribute in a survey sampling have been introduced. The proposed estimators are compared with the recent estimator proposed by Odumade and Singh [Efficient use of two decks of cards in randomized response sampling, Comm. Statist. Theory Methods 38 (2009), pp. 439–446] and Warner [Randomized response: A survey technique for eliminating evasive answer bias, J. Amer. Statist. Assoc. 60 (1965), pp. 63–69].     

Incorporating Time‐Dose‐Response into Legionella Outbreak Models

A novel method was used to incorporate in vivo host–pathogen dynamics into a new robust outbreak model for legionellosis. Dose‐response and time‐dose‐response (TDR) models were generated for Legionella longbeachae exposure to mice via the intratracheal route using a maximum likelihood estimation approach. The best‐fit TDR model was then incorporated into two L. pneumophila outbreak models: an outbreak that occurred at a spa in Japan, and one that occurred in a Melbourne aquarium. The best‐fit TDR from the murine dosing study was the beta‐Poisson with exponential‐reciprocal dependency model, which had a minimized deviance of 32.9. This model was tested against other incubation distributions in the Japan outbreak, and performed consistently well, with reported deviances ranging from 32 to 35. In the case of the Melbourne outbreak, the exponential model with exponential dependency was tested against non‐time‐dependent distributions to explore the performance of the time‐dependent model with the lowest number of parameters. This model reported low minimized deviances around 8 for the Weibull, gamma, and lognormal exposure distribution cases. This work shows that the incorporation of a time factor into outbreak distributions provides models with acceptable fits that can provide insight into the in vivo dynamics of the host‐pathogen system.