The challenges of evaluating dose response in flexible‐dose trials using marginal structural models

Assessing dose response from flexible‐dose clinical trials is problematic. The true dose effect may be obscured and even reversed in observed data because dose is related to both previous and subsequent outcomes. To remove selection bias, we propose marginal structural models, inverse probability of treatment‐weighting (IPTW) methodology. Potential clinical outcomes are compared across dose groups using a marginal structural model (MSM) based on a weighted pooled repeated measures analysis (generalized estimating equations with robust estimates of standard errors), with dose effect represented by current dose and recent dose history, and weights estimated from the data (via logistic regression) and determined as products of (i) inverse probability of receiving dose assignments that were actually received and (ii) inverse probability of remaining on treatment by this time. In simulations, this method led to almost unbiased estimates of true dose effect under various scenarios. Results were compared with those obtained by unweighted analyses and by weighted analyses under various model specifications. The simulation showed that the IPTW MSM methodology is highly sensitive to model misspecification even when weights are known. Practitioners applying MSM should be cautious about the challenges of implementing MSM with real clinical data. Clinical trial data are used to illustrate the methodology. Copyright © 2012 John Wiley & Sons, Ltd.     

Optional randomized response technique in two-phase sampling

Two-phase optional randomized response (TORR) technique has been proposed. The proposed randomized response (RR) performs much better in general than the existing RR techniques. Theoretical and numerical illustrations identified conditions of superiority of the proposed TORR over the existing comparable optional randomized response (ORR) techniques.     

Dependence Assessment in Human Reliability Analysis Using Evidence Theory and AHP

Dependence assessment among human errors in human reliability analysis (HRA) is an important issue. Many of the dependence assessment methods in HRA rely heavily on the expert's opinion, thus are subjective and may sometimes cause inconsistency. In this article, we propose a computational model based on the Dempster‐Shafer evidence theory (DSET) and the analytic hierarchy process (AHP) method to handle dependence in HRA. First, dependence influencing factors among human tasks are identified and the weights of the factors are determined by experts using the AHP method. Second, judgment on each factor is given by the analyst referring to anchors and linguistic labels. Third, the judgments are represented as basic belief assignments (BBAs) and are integrated into a fused BBA by weighted average combination in DSET. Finally, the CHEP is calculated based on the fused BBA. The proposed model can deal with ambiguity and the degree of confidence in the judgments, and is able to reduce the subjectivity and improve the consistency in the evaluation process.     

On the application of statistical learning approaches to construct inverse probability weights in marginal structural Cox models: Hedging against weight-model misspecification

The marginal structural Cox model (MSCM) estimates can be highly sensitive to weight-model misspecification. We assess the performance of various popular statistical learners, such as LASSO, support vector machines, CART, bagged CART, and boosted CART, in estimating MSCM weights. When weight-models are misspecified, we find that the weights computed from boosted CART generally lead to less MSE and better coverage for the MSCM estimates. This study is motivated by the investigation of the impact of beta-interferon treatment on disability progression in subjects with multiple sclerosis from British Columbia, Canada (1995–2008).     

Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT

We propose inverse probability weighted estimators for the local average treatment effect (LATE) and the local average treatment effect for the treated (LATT) under instrumental variable assumptions with covariates. We show that these estimators are asymptotically normal and efficient. When the (binary) instrument satisfies one-sided noncompliance, we propose a Durbin–Wu–Hausman-type test of whether treatment assignment is unconfounded conditional on some observables. The test is based on the fact that under one-sided noncompliance LATT coincides with the average treatment effect for the treated (ATT). We conduct Monte Carlo simulations to demonstrate, among other things, that part of the theoretical efficiency gain afforded by unconfoundedness in estimating ATT survives pretesting. We illustrate the implementation of the test on data from training programs administered under the Job Training Partnership Act in the United States. This article has online supplementary material.     

An Extension of Sampford's Method for Unequal Probability Sampling

Abstract. Sampford's unequal probability sampling method is extended to the case that the inclusion probabilities do not sum to an integer. In this case, the sampling outcome is left open for exactly one randomly chosen unit and that unit gets a new inclusion probability. Three applications are presented. Two of them challenge traditional sampling routines. The simple Pareto sampling design, which was introduced by Rosén in 1997, is also extended. The extended Pareto design is shown to be close to the extended Sampford design.     

A note on the unimddality of discrete distributions

It is noted that the unimadility property is very inportant and necessary in many probabilistic-statistical models. In this paper, we consider the definition of discrete uniirodality such that the mode may be unique integer or a sequence of consecutive integers. It will be shown that the necessary and sufficient condition for the discrete distribution to be uninnodal about a can be given through some canonical representation of its characteristic function ‘ch.f.’ Further, characterization results for some well-known distributions are established.     

A characterization of a bimodal distribution

As a sequel to Khlnchirie's definition of unimodality a bimodal distribution function is defined, A characterization for such a distribution is given using the well-known result of Khinchine on unimodality and a characterization theorem for a U-shaped probability density function by Ghosh and Shanbhag(1972).     

关于τ（α）函数在概率积分计算中的应用

本文通过τ（α）函数性质及τ（α）函数与B（P,q）函数的关系,得出了τ（α）函数的一系列特殊值,结合概率积分的特点,应用τ（α）函数与B（P,q）函数计算一些概率积分．     

服务失误归因对服务补救和补救满意度关系的影响

服务的特殊性使得服务质量并非产品质量那样可以得到有效控制,很多因素都可能引发服务失败,此时,企业必须及时采取补救措施,努力消除顾客的负面情绪,避免顾客的流失。补救措施本身并非无差异,在进行服务补救时,认识服务补救的有效性对企业至关重要。文章在回顾服务失误,服务补救以及补救满意度文献的基础上,从服务补救、服务补救满意度的关系出发,在研究模型中引入了服务失误归因的影响,使得服务补救的理论研究更为完善,为企业后续的服务补救管理提供指导。