No abstract

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. American Statistical Association is collaborating with JSTOR to digitize, preserve and extend access to Journal of the American Statistical Association.We study Bayesian models and methods for analysing network traffic counts in problems of inference about the traffic intensity between directed pairs of origins and destinations in networks. This is a class of problems very recently discussed by Vardi in a 1996 JASA article and is of interest in both communication and transportation network studies. The current article develops the theoretical framework of variants of the origin-destination flow problem and introduces Bayesian approaches to analysis and inference. In the first, the so-called fixed routing problem, traffic or messages pass between nodes in a network, with each message originating at a specific source node, and ultimately moving through the network to a predetermined destination node. All nodes are candidate origin and destination points. The framework assumes no travel time complications, considering only the number of messages passing between pairs of nodes in a specified time interval. The route count, or route flow, problem is to infer the set of actual number of messages passed between each directed origin-destination pair in the time interval, based on the observed counts flowing between all directed pairs of adjacent nodes. Based on some development of the theoretical structure of the problem and assumptions about prior distributional forms, we develop posterior distributions for inference on actual origin-destination counts and associated flow rates. This involves iterative simulation methods, or Markov chain Monte Carlo (MCMC), that combine Metropolis-Hastings steps within an overall Gibbs sampling framework. We discuss issues of convergence and related practical matters, and illustrate the approach in a network previously studied in Vardi's article. We explore both methodological and applied aspects much further in a concrete problem of a road network in North Carolina, studied in transportation flow assessment contexts by civil engineers. This investigation generates critical insight into limitations of statistical analysis, and particularly of non-Bayesian approaches, due to inherent structural features of the problem. A truly Bayesian approach, imposing partial stochastic constraints through informed prior distributions, offers a way of resolving these problems and is consistent with prevailing trends in updating traffic flow intensities in this field. Following this, we explore a second version of the problem that introduces elements of uncertainty about routes taken by individual messages in terms of Markov selection of outgoing links for messages at ...

(2014) Safety and efficacy of aerobic training in operable breast cancer patients receiving neoadjuvant chemotherapy: A phase II randomized trial, Acta Oncologica, 53:1, 65-74,

BACKGROUND. A feasibility study examining the effects of supervised aerobic exercise training on cardiopulmonary and quality of life (QOL) endpoints among postsurgical nonsmall cell lung cancer (NSCLC) patients was conducted. METHODS. Using a single‐group design, 20 patients with stage I‐IIIB NSCLC performed 3 aerobic cycle ergometry sessions per week at 60% to 100% of peak workload for 14 weeks. Peak oxygen consumption (VO2peak) was assessed using an incremental exercise test. QOL and fatigue were assessed using the Functional Assessment of Cancer Therapy–Lung (FACT‐L) scale. RESULTS. Nineteen patients completed the study. Intention‐to‐treat analysis indicated that VO2peak increased 1.1 mL/kg−1/min−1 (95% confidence interval [CI], −0.3‐2.5; P = .109) and peak workload increased 9 W (95% CI, 3‐14; P = .003), whereas FACT‐L increased 10 points (95% CI, −1‐22; P = .071) and fatigue decreased 7 points (95% CI; −1 to −17; P = .029) from baseline to postintervention. Per protocol analyses indicated greater improvements in cardiopulmonary and QOL endpoints among patients not receiving adjuvant chemotherapy. CONCLUSIONS. This pilot study provided proof of principle that supervised aerobic training is safe and feasible for postsurgical NSCLC patients. Aerobic exercise training is also associated with significant improvements in QOL and select cardiopulmonary endpoints, particularly among patients not receiving chemotherapy. Larger randomized trials are warranted. Cancer 2008. © 2008 American Cancer Society.