Extending the Mann–Whitney–Wilcoxon rank sum test to longitudinal regression analysis

Outliers are commonly observed in psychosocial research, generally resulting in biased estimates when comparing group differences using popular mean-based models such as the analysis of variance model. Rank-based methods such as the popular Mann–Whitney–Wilcoxon (MWW) rank sum test are more effective to address such outliers. However, available methods for inference are limited to cross-sectional data and cannot be applied to longitudinal studies under missing data. In this paper, we propose a generalized MWW test for comparing multiple groups with covariates within a longitudinal data setting, by utilizing the functional response models. Inference is based on a class of U-statistics-based weighted generalized estimating equations, providing consistent and asymptotically normal estimates not only under complete but missing data as well. The proposed approach is illustrated with both real and simulated study data.     

From Amazon to Apple: Modeling Online Retail Sales,Purchase Incidence,and Visit Behavior

In this study, we propose a multivariate stochastic model for Web site visit duration, page views, purchase incidence, and the sale amount for online retailers. The model is constructed by composition from carefully selected distributions and involves copula components. It allows for the strong nonlinear relationships between the sales and visit variables to be explored in detail, and can be used to construct sales predictions. The model is readily estimated using maximum likelihood, making it an attractive choice in practice given the large sample sizes that are commonplace in online retail studies. We examine a number of top-ranked U.S. online retailers, and find that the visit duration and the number of pages viewed are both related to sales, but in very different ways for different products. Using Bayesian methodology, we show how the model can be extended to a finite mixture model to account for consumer heterogeneity via latent household segmentation. The model can also be adjusted to accommodate a more accurate analysis of online retailers like apple.com that sell products at a very limited number of price points. In a validation study across a range of different Web sites, we find that the purchase incidence and sales amount are both forecast more accurately using our model, when compared to regression, probit regression, a popular data-mining method, and a survival model employed previously in an online retail study. Supplementary materials for this article are available online.     

Asymptotic Comparison Between Constant-stress Testing and Step-stress Testing for Type-I Censored Data from Exponential Distribution

By running the life tests at higher stress levels than normal operating conditions, accelerated life testing quickly yields information on the lifetime distribution of a test unit. The lifetime at the design stress is then estimated through extrapolation using a regression model. In constant-stress testing, a unit is tested at a fixed stress level until failure or the termination time point of the test, while step-stress testing allows the experimenter to gradually increase the stress levels at some pre-fixed time points during the test. In this article, the optimal k-level constant-stress and step-stress accelerated life tests are compared for the exponential failure data under Type-I censoring. The objective is to quantify the advantage of using the step-stress testing relative to the constant-stress one. A log-linear relationship between the mean lifetime parameter and stress level is assumed and the cumulative exposure model holds for the effect of changing stress in step-stress testing. The optimal design point is then determined under C-optimality, D-optimality, and A-optimality criteria. The efficiency of step-stress testing compared to constant-stress testing is discussed in terms of the ratio of optimal objective functions based on the information matrix.     

On Variational Bayes Estimation and Variational Information Criteria for Linear Regression Models

Variational Bayes (VB) estimation is a fast alternative to Markov Chain Monte Carlo for performing approximate Baesian inference. This procedure can be an efficient and effective means of analyzing large datasets. However, VB estimation is often criticised, typically on empirical grounds, for being unable to produce valid statistical inferences. In this article we refute this criticism for one of the simplest models where Bayesian inference is not analytically tractable, that is, the Bayesian linear model (for a particular choice of priors). We prove that under mild regularity conditions, VB based estimators enjoy some desirable frequentist properties such as consistency and can be used to obtain asymptotically valid standard errors. In addition to these results we introduce two VB information criteria: the variational Akaike information criterion and the variational Bayesian information criterion. We show that variational Akaike information criterion is asymptotically equivalent to the frequentist Akaike information criterion and that the variational Bayesian information criterion is first order equivalent to the Bayesian information criterion in linear regression. These results motivate the potential use of the variational information criteria for more complex models. We support our theoretical results with numerical examples.     

Preserving the Scholarly Collection: An Examination of the Perpetual Access Clauses in the Texas A&M University Libraries' Major E-Journal Licenses

Librarians are urged to lobby for the inclusion of perpetual access clauses during license negotiations and to examine existing contracts to ensure that perpetual access provisions are clearly understood and achievable. The authors analyzed the perpetual access clauses in nineteen of the Texas A&M University Libraries' licenses for electronic journal packages to determine the exact provisions granted, and found that the Libraries do not really know what access to previously subscribed content will entail. This raises profound concerns about the Libraries' ability to provide meaningful perpetual access to previously subscribed content to its users in the current environment.     

The role of dualities in arbitrating continuity and change in forms of organizing

A substantial body of literature on new forms of organizing has forecast the end of bureaucracy. More recent empirical studies, however, indicate that high‐performing organizations are adopting dual forms of organizing in which the controllability advantages associated with traditional forms work to complement and support the responsiveness attributes of new forms of organizing. The paradox is that, if organizations discard the key planning, co‐ordinating and direction‐setting mechanisms of traditional forms of organizing, they also remove the stabilizing dimensions of organizational form that are essential in periods of uncertainty and change. The challenge for organizations lies in learning how to manage the tensions or dualities between traditional and new forms of organizing, a process demanding the arbitration of continuity and change. This paper explores the concept of dualities and its salience in the management of organizing forms. First, the nature of dualities is explained; secondly, a set of characteristics is developed to describe the behaviour of dualities; and thirdly, suggestions are presented for arbitrating the tensions that exist in organizing form dualities. These three contributions are relevant because they signal the route to the effective creation and management of organizing form dualities, the benefit of which is the constructive combination of dynamic capabilities (underpinning innovation and responsiveness, the hallmarks of new forms of organizing) and operational capabilities (underpinning stability and efficiency, the hallmarks of traditional forms of organizing).     

Estimating Consumer Exposure to PFOS and PFOA

Perfluorinated compounds have been used for more than 50 years as process aids, surfactants, and for surface protection. This study is a comprehensive assessment of consumer exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) from a variety of environmental and product-related sources. To identify relevant pathways leading to consumer exposure to PFOS and PFOA a scenario-based approach has been applied. Scenarios represent realistic situations where age- and gender-specific exposure occurs in the everyday life of consumers. We find that North American and European consumers are likely to experience ubiquitous and long-term uptake doses of PFOS and PFOA in the range of 3 to 220 ng per kg body weight per day (ng/kg_bw/day) and 1 to 130 ng/kg_bw/day, respectively. The greatest portion of the chronic exposure to PFOS and PFOA is likely to result from the intake of contaminated foods, including drinking water. Consumer products cause a minor portion of the consumer exposure to PFOS and PFOA. Of these, it is mainly impregnation sprays, treated carpets in homes, and coated food contact materials that may lead to consumer exposure to PFOS and PFOA. Children tend to experience higher total uptake doses (on a body weight basis) than teenagers and adults because of higher relative uptake via food consumption and hand-to-mouth transfer of chemical from treated carpets and ingestion of dust. The uptake estimates based on scenarios are within the range of values derived from blood serum data by applying a one-compartment pharmacokinetic model.     

Perceptions of Ecological Risk Associated with Mountain Pine Beetle (Dendroctonus ponderosae) Infestations in Banff and Kootenay National Parks of Canada

Western Canada is experiencing an unprecedented outbreak of the mountain pine beetle (MPB). The MPB has the potential to impact some of Canada's national parks by affecting park ecosystems and the visitor experience. Controls have been initiated in some parks to lessen the impacts and to prevent the beetle from spreading beyond park boundaries. We examine the perception of ecological risk associated with MPB in two of Canada's national parks, the factors affecting perceptions of risk, and the influence of risk judgments on support for controlling MPB outbreaks in national parks. Data were collected using two studies of park visitors: a mail survey in 2003 and an onsite survey in 2005. The MPB was rated as posing a greater risk to the health and productivity of park ecosystems than anthropogenic hazards and other natural disturbance agents. Visitors who were familiar with MPB rated the ecological and visitor experience impacts as negative, unacceptable, and eliciting negative emotion. Knowledge and residency were the most consistent predictors of risk judgments. Of knowledge, risk, and demographic variables, only sex and risk to ecosystem domains influenced support for controlling the MPB in national parks. Implications for managing MPB in national parks, visitor education, and ecological integrity are discussed.