Principal point classification: Applications to differentiating drug and placebo responses in longitudinal studies

Principal points are cluster means for theoretical distributions. A discriminant methodology based on principal points is introduced. The principal point classification method is useful in clinical trials where the goal is to distinguish and differentiate between different treatment effects. Particularly, in psychiatric studies where placebo response rates can be very high, the principal point classification is illustrated to distinguish specific drug responders from non-specific placebo responders.     

Formative research methods to understand patient and provider responses to heart attack symptoms

Formative research is often required for program planning, and for reducing uncertainty about generalizability of program effects. This article describes and justifies methods of formative research conducted for the REACT study (Rapid Early Action for Coronary Treatment), a multi-center collaborative randomized community trial aimed at reducing patient delay in seeking care for acute myocardial infarction (AMI). Formative research cast light on patient and community members’ decision-making process in seeking help for AMI, as well as barriers and facilitators of this process. Investigators at all five REACT Field Centers participated in the formative research. The process consisted of: (1) developing a common theoretical framework for the study intervention; (2) conducting a literature review and qualitative research to identify and address gaps in knowledge; and (3) developing a common protocol for the REACT study that accommodated the diversity of the target communities in terms of services, resources, history, and ethnicity. Analysis employed triangulation, defined as an explicit search for heterogeneous data sources to reduce uncertainty about forces at work and opportunities for intervention across settings and populations. Because the collection and interpretation of data went in stages, staff of several REACT Field Centers had independent input to the overall synthesis, then shared and revised the results. Advantages and limitations of this approach are discussed.     

Accommodating stochastic departures from percentile invariance in causal models

Summary.  Consider a clinical trial in which participants are randomized to a single-dose treatment or a placebo control and assume that the adherence level is accurately recorded. If the treatment is effective, then good adherers in the treatment group should do better than poor ad- herers because they received more drug; the treatment group data follow a dose–response curve. But, good adherers to the placebo often do better than poor adherers, so the observed adherence–response in the treatment group cannot be completely attributed to the treatment. Efron and Feldman proposed an adjustment to the observed adherence–response in the treatment group by using the adherence–response in the control group. It relies on a percentile invariance assumption under which each participant's adherence percentile within their assigned treatment group does not depend on the assigned group (active drug or placebo). The Efron and Feldman approach is valid under percentile invariance, but not necessarily under departures from it. We propose an analysis based on a generalization of percentile invariance that allows adherence percentiles to be stochastically permuted across treatment groups, using a broad class of stochastic permutation models. We show that approximate maximum likelihood estimates of the underlying dose–response curve perform well when the stochastic permutation process is correctly specified and are quite robust to model misspecification.     

Using statistical techniques to detect fraud: a test case

In an experiment to test the effectiveness of statistical measures in detecting fraud, three physicians fabricated scores on the Montgomery–Åsberg Depression Rating Scale (MADRS) for a number of subjects in three sites. The fabricated data were then planted among MADRS data from 18 genuine sites. A statistician blinded as to the identity and quantity of the fabricated data attempted to detect the ‘fraudulent’ data by searching for unusual means and correlations. One of the three fabricated sites was correctly identified, and one genuine site was incorrectly identified as a potential fabrication. In addition, inlying and/or outlying means and correlations found in the genuine data suggested the possibility of using statistical checks for unusual data early in a study so that sites with unusual patterns could be prioritized for monitoring, training and, if necessary, auditing. Copyright © 2004 John Wiley & Sons Ltd.     

电子阅览室读者群的实证分析

以电子阅览室上机者为研究对象,对原始数据进行聚类和逐步拟合回归分析,研究结果显示:2004年6月份上机的读者群具有学习和娱乐两大特点.     

Testing for ordered failure rates under general progressive censoring

For exponentially distributed failure times under general progressive censoring schemes, testing procedures for ordered failure rates are proposed using the likelihood ratio principle. Constrained maximum likelihood estimators of the failure rates are found. The asymptotic distributions of the test statistics are shown to be mixtures of chi-square distributions. When testing the equality of the failure rates, a simulation study shows that the proposed test with restricted alternative has improved power over the usual chi-square statistic with an unrestricted alternative. The proposed methods are illustrated using data of survival times of patients with squamous carcinoma of the oropharynx.     

Adaptive sampling without replacement of clusters

In a common form of adaptive cluster sampling, an initial sample of units is selected by random sampling without replacement and, whenever the observed value of the unit is sufficiently high, its neighboring units are added to the sample, with the process of adding neighbors repeated if any of the added units are also high valued. In this way, an initial selection of a high-valued unit results in the addition of the entire network of surrounding high-valued units and some low-valued “edge” units where sampling stops. Repeat selections can occur when more than one initially selected unit is in the same network or when an edge unit is shared by more than one added network. Adaptive sampling without replacement of networks avoids some of this repeat selection by sequentially selecting initial sample units only from the part of the population not already in any selected network. The design proposed in this paper carries this step further by selecting initial units only from the population, exclusive of any previously selected networks or edge units.     

Dynamic allocation as a balancing act

The CPMP Points to Consider on Adjustment for Baseline Covariates recently came into operation. As well as providing sound guidance, this document states a strong position against dynamic allocation. This paper reviews the most important issues involved and aims to stimulate interest in further investigating alternative allocation methods in clinical trials. Copyright © 2004 John Wiley & Sons, Ltd.     

Excel编程在随机分班考试中的应用

随机分班与考试牌的应用可有效防范考试中的作弊和违纪行为。运用Excel电子表程序的编程功能 ,建立学生名单数据库和具备随机分班功能的实用程序 ,并可迅速查询 -打印成分班名单。该程序使用方便 ,快速 ,15～ 2 0min内对 12 0人考生随机分班和考试牌组合。