刑事案件普通程序简易审若干问题探讨

对被告人认罪的案件适用普通程序简易审,有利于节约司法资源和提高诉讼效率,文章对刑事案件普通程序简易审中的若干实际操作问题提出了具体设计,并要求建立相关制度保障。     

Repeated Confidence Intervals Under Fractional Brownian Motion in Long-Term Clinical Trials

Repeated confidence interval (RCI) is an important tool for design and monitoring of group sequential trials according to which we do not need to stop the trial with planned statistical stopping rules. In this article, we derive RCIs when data from each stage of the trial are not independent thus it is no longer a Brownian motion (BM) process. Under this assumption, a larger class of stochastic processes fractional Brownian motion (FBM) is considered. Comparisons of RCI width and sample size requirement are made to those under Brownian motion for different analysis times, Type I error rates and number of interim analysis. Power family spending functions including Pocock, O'Brien-Fleming design types are considered for these simulations. Interim data from BHAT and oncology trials is used to illustrate how to derive RCIs under FBM for efficacy and futility monitoring.     

Longitudinal covariate-adjusted response-adaptive randomized designs

Clinical trials often involve longitudinal data set which has two important characteristics: repeated and correlated measurements and time-varying covariates. In this paper, we propose a general framework of longitudinal covariate-adjusted response-adaptive (LCARA) randomization procedures. We study their properties under widely satisfied conditions. This design skews the allocation probabilities which depend on both patients' first observed covariates and sequentially estimated parameters based on the accrued longitudinal responses and covariates. The asymptotic properties of estimators for the unknown parameters and allocation proportions are established. The special case of binary treatment and continuous responses is studied in detail. Simulation studies and an analysis of the National Cooperative Gallstone Study (NCGS) data are carried out to illustrate the advantages of the proposed LCARA randomization procedure.     

The interference of paid work with household demands in different social policy contexts: perceived work-household conflict in Sweden, the UK, the Netherlands, Hungary, and the Czech Republic

The article explores whether people experiences a lower level of work-household conflict in a context that is characterized by extensive family policies (Sweden and to some extent Hungary and Czech Republic) aimed at facilitating participation in the labour market. This is done by studying perceived work-household conflict among women and men living in Sweden, the UK, the Netherlands, Hungary, and the Czech Republic. The analyses are based on the answers to a questionnaire distributed to nearly 6,000 randomly selected individuals within the framework of the European Union financed 'Household, Work, and Flexibility' (HWF) study. The results show that women in Sweden experience conflicts between work and household demands to a higher degree than any other category in all five countries. The differences between Swedish women and women living in the Netherlands and the UK are explained by variables indicating qualifications and workload in the main job, but the lower degree of work-household conflict among Czech and Hungarian women is still significant when controlling for household composition and working conditions. Data indicate that a possible explanation for this can be found in the interplay between men's and women's attitudes toward gender roles and the actual situation in terms of division of labour.     

An approach to use of an adaptive procedure to clinical trials for molecularly heterogenous subject selection at interim

Abstract

For clinical trials, molecular heterogeneity has played a more important role recently. Many novel clinical trial designs prospectively incorporate molecular information to evaluation of treatment effects. In this paper, an adaptive procedure incorporating a non-pre-specified genomic biomarker is employed in the interim of a conventional trial. A non-pre-specified binary genomic biomarker, which is predictive of treatment effect, is used to classify study patients into two mutually exclusive subgroups at the interim review. According to the observations at the interim stage, adaptations such as adjusting sample size or shifting eligibility of study patients are then made in case of different scenarios.     

A bivariate Bayesian dose‐finding procedure applied to a seamless phase I/II trial in rheumatoid arthritis

We describe a dose escalation procedure for a combined phase I/II clinical trial. The procedure is based on a Bayesian model for the joint distribution of the occurrence of a dose limiting event and of some indicator of efficacy (both considered binary variables), making no assumptions other than monotonicity. Thus, the chances of each outcome are assumed to be non‐decreasing in dose level. We applied the procedure to the design of a placebo‐controlled, sequential trial in rheumatoid arthritis, in each stage of which patients were randomized between placebo and all dose levels that currently appeared safe and non‐futile. On the basis of data from a pilot study, we constructed five different scenarios for the dose–response relationships under which we simulated the trial and assessed the performance of the procedure. The new design appears to have satisfactory operating characteristics and can be adapted to the requirements of a range of trial situations. Copyright © 2012 John Wiley & Sons, Ltd.     

初婚夫妇年龄差的特点、变动趋势及分析——以北京为例

利用北京市2004～2009年的婚姻登记数据,对近年来初婚夫妇年龄差的特点和变动趋势进行考察,并探讨其影响因素。研究发现,近年来北京市初婚夫妇的平均年龄差为1.87岁,"男大女小"仍是主流的婚龄匹配模式,但由于"妻大于夫"的夫妇数量的增多和大年龄差距的"夫大于妻"的情况的减少,夫妇年龄差呈逐渐缩小的态势。女性初婚年龄的推迟、女性教育文化水平的不断提升及其与男性学历差距的缩小、城市化进程的不断推进等,均使夫妇年龄差趋于缩小。这些发现有助于我们了解当前大城市的婚配状况和发展态势,并为进一步的深入研究提供依据。     

Sample size allocation in multiregional equivalence studies

With the increasing globalization of drug development, the multiregional clinical trial (MRCT) has gained extensive use. The data from MRCTs could be accepted by regulatory authorities across regions and countries as the primary sources of evidence to support global marketing drug approval simultaneously. The MRCT can speed up patient enrollment and drug approval, and it makes the effective therapies available to patients all over the world simultaneously. However, there are many challenges both operationally and scientifically in conducting a drug development globally. One of many important questions to answer for the design of a multiregional study is how to partition sample size into each individual region. In this paper, two systematic approaches are proposed for the sample size allocation in a multiregional equivalence trial. A numerical evaluation and a biosimilar trial are used to illustrate the characteristics of the proposed approaches.     

Design considerations in clinical trials with cure rate survival data: A case study in oncology

For clinical trials with time‐to‐event as the primary endpoint, the clinical cutoff is often event‐driven and the log‐rank test is the most commonly used statistical method for evaluating treatment effect. However, this method relies on the proportional hazards assumption in that it has the maximal power in this circumstance. In certain disease areas or populations, some patients can be curable and never experience the events despite a long follow‐up. The event accumulation may dry out after a certain period of follow‐up and the treatment effect could be reflected as the combination of improvement of cure rate and the delay of events for those uncurable patients. Study power depends on both cure rate improvement and hazard reduction. In this paper, we illustrate these practical issues using simulation studies and explore sample size recommendations, alternative ways for clinical cutoffs, and efficient testing methods with the highest study power possible.     

Notes on interval estimation of the proportion ratio under a three-treatment three-period crossover trial

When comparing two experimental treatments with a placebo, we focus our attention on interval estimation of the proportion ratio (PR) of patient responses under a three-period crossover design. We propose a random effects exponential multiplicative risk model and derive asymptotic interval estimators in closed form for the PR between treatments and placebo. Using Monte Carlo simulations, we compare the performance of these interval estimators in a variety of situations. We use the data comparing two different doses of an analgesic with placebo for the relief of primary dysmenorrhea to illustrate the use of these interval estimators and the difference in estimates of the PR and odds ratio (OR) when the underlying relief rates are not small.