Optimal adaptive designs for acute oral toxicity assessment

Acute oral toxicity studies are used to assess the toxicity to experimental animals of a single dose of the substance under investigation, assigning the substance to one of a number of classes. Animal welfare concerns have led to the development of three adaptive designs as alternatives to the traditional fixed sample design. These lead to reductions in the number of animals required in total and in the number exposed to lethal doses. In this paper, we show how designs can be constructed to optimise utility functions combining the need to classify correctly with the desire to use a small number of animals. Constrained optimal designs are also obtained in which no animal is exposed to a dose higher than that at which a death has been observed. The optimal designs lead to the correct classification with high probability whilst reducing the expected number of animal deaths relative to existing adaptive designs.     

On implementing Jeffreys' substitution likelihood for Bayesian inference concerning the medians of unknown distributions

When statisticians are uncertain as to which parametric statistical model to use to analyse experimental data, they will often resort to a non-parametric approach. The purpose of this paper is to provide insight into a simple approach to take when it is unclear as to the appropriate parametric model and plan to conduct a Bayesian analysis. I introduce an approximate, or substitution likelihood, first proposed by Harold Jeffreys in 1939 and show how to implement the approach combined with both a non-informative and an informative prior to provide a random sample from the posterior distribution of the median of the unknown distribution. The first example I use to demonstrate the approach is a within-patient bioequivalence design and then show how to extend the approach to a parallel group design.     

Estimation and Testing of Learning Curves

This article describes a new approach to learning curve estimation. Our approach is to formulate statistical procedures that conform to alternative learning curve theories. This leads to the development of nonlinear statistical models of the learning curves. For the three data sets analyzed, autocorrelation seems to be an important problem. Parameter estimates were derived using the maximum likelihood principle in the presence of first-order autocorrelation. Nonnested tests were used to select the appropriate formulation of the learning curve. Research conclusions are to use unit data when estimating a learning curve and to be prepared to treat autocorrelation if present.     

Hypothesis testing for the dispersion parameter of the hyper-Poisson regression model

The Poisson distribution is widely used to deal with count data, however, it is unable to capture the dispersion problems. The hyper-Poisson distribution is a particular case of the extended Conway–Maxwell distribution which takes into account the dispersion phenomena of the count data. The main motivation to consider this model is the possibility to link the mean to the regressor variables in very natural way to solve testing problems. So, this paper will be focalized in the gradient statistics to detect dispersions and to compare with the classical likelihood ratio statistic. Two illustrative applications are considered.     

城市基本公共服务面向农民工开放度测量研究

2016年1月起实施的《居住证暂行条例》从根本上摒弃了农民工享有城市基本公共服务的制度桎梏，但农民工实际所能享有的水平尚取决于城市政府开放其公共服务的程度，包括“承诺”服务的领域多少和所设置的约束“条件”高低。本文以各城市居住证管理制度文件为依据，运用全国流动人口调查数据，测量城市基本公共服务面向农民工群体的开放度。结果显示：（1）城市基本公共服务全部领域超过一半面向农民工开放，开放度0.5076。即便在排他性服务领域，也超过1/3面向农民工开放，开放度达到0.3569，农民工开始实质性享有城市基本公共服务，但离平等权利仍有距离；（2）开放度在区域间的分布表现为东部城市低于中部城市更低于西部城市、直辖市低于省会城市更低于其他地级市，珠三角、长三角和京津冀城市低于三大经济圈外城市。相对发达的城市开放度更低，反映出开放度高低主要取决于城市政府的开放意愿而非提供服务的能力；（3）开放限制主要来源于“条件”约束，城市政府在排他性服务领域的承诺度0.7703，承诺服务的领域超过3/4。但约束度达0.4502，城市政府只向其中54.98%能满足约束条件的农民工开放所承诺的服务，源自约束条件的限制占到开放限制的60%以上。城市政府遵循居住证制度规范面向外来人口统一“承诺”服务，但通过“条件”约束选择性地限制了农民工获得城市基本公共服务的机会，农民工平等权利的最终实现尚需要政策制度的系统性配套改革。     

A Bayesian model for estimating the malaria transition probabilities considering individuals lost to follow-up

It is known that patients may cease participating in a longitudinal study and become lost to follow-up. The objective of this article is to present a Bayesian model to estimate the malaria transition probabilities considering individuals lost to follow-up. We consider a homogeneous population, and it is assumed that the considered period of time is small enough to avoid two or more transitions from one state of health to another. The proposed model is based on a Gibbs sampling algorithm that uses information of lost to follow-up at the end of the longitudinal study. To simulate the unknown number of individuals with positive and negative states of malaria at the end of the study and lost to follow-up, two latent variables were introduced in the model. We used a real data set and a simulated data to illustrate the application of the methodology. The proposed model showed a good fit to these data sets, and the algorithm did not show problems of convergence or lack of identifiability. We conclude that the proposed model is a good alternative to estimate probabilities of transitions from one state of health to the other in studies with low adherence to follow-up.     

Prediction for generalized linear models

Regression models are often used to make predictions. All the information needed is contained in the predictive distribution. However, this cannot be evaluated explicitly for most generalized linear models. We construct two approximations to this distribution and demonstrate their use on two sets of survival data, corresponding to the outcome of patients admitted to intensive care units and the survival times of leukaemia patients.Regression models are often used to make predictions. All the information needed is contained in the predictive distribution. However, this cannot be evaluated explicitly for most generalized linear models. We construct two approximations to this distribution and demonstrate their use on two sets of survival data, corresponding to the outcome of patients admitted to intensive care units and the survival times of leukaemia patients.Regression models are often used to make predictions. All the information needed is contained in the predictive distribution. However, this cannot be evaluated explicitly for most generalized linear models. We construct two approximations to this distribution and demonstrate their use on two sets of survival data, corresponding to the outcome of patients admitted to intensive care units and the survival times of leukaemia patients.Regression models are often used to make predictions. All the information needed is contained in the predictive distribution. However, this cannot be evaluated explicitly for most generalized linear models. We construct two approximations to this distribution and demonstrate their use on two sets of survival data, corresponding to the outcome of patients admitted to intensive care units and the survival times of leukaemia patients.     

On a redundant repairable system with switching failure: Bayesian approach

System characteristics of a redundant repairable system are studied from a Bayesian viewpoint with different types of priors assumed for the unknown parameters. The system consists of two primary units, one standby unit, and one repair facility which is activated when switching to standby fails. Times to failure and times to repair of the operating units are assumed to follow exponential distributions. When time to failure and time to repair have uncertain parameters, a Bayesian approach is adopted to evaluate system characteristics. Monte Carlo simulation is used to derive the posterior distribution for the mean time to system failure and steady-state availability. Some numerical experiments are performed to illustrate the results derived in this paper.     

我国35个大中城市房价-持久收入比研究

房价收入比是反映居民购房可支付能力的重要指标。为了更真实准确反映我国居民长期承受的购房负担,本文基于持久收入假说,利用我国35个大中城市数据,建立状态空间模型,估计出持久收入意义下的房价收入比,通过情景分析确定其合理上限,并分析主要特征。研究表明：①我国房价-持久收入比的合理上限为7.6,2002-2013年35个大中城市的房价-持久收入比均值是9.2,其中28个城市已超过该上限,比值最高的北京已达到14.9;②城市越发达,则房价-持久收入比越高,居民需要承受的购房压力越大,且在时间趋势上,一线与二三线城市间的差距呈现扩大趋势;③在地理分布上,我国东部、中部、东北地区、西部大中城市的房价-持久收入比呈现从高到低的排列顺序;④相比于传统方法中根据可支配收入测算的房价收入比,房价-持久收入比与其约有10%的差异。当前我国政府应采取有效措施继续限制房价,减轻居民购房负担。     

A response to M. Stone: 'How not to measure the efficiency of public services (and how one might)'

Summary.  This is a response to Stone's criticisms of the Spottiswoode report to the UK Treasury which was responding to the Treasury's request for improved methods to evaluate the efficiency and productivity of the 43 police districts in England and Wales. The Spottiswoode report recommended uses of data envelopment analysis (DEA) and stochastic frontier analysis (SFA), which Stone critiqued en route to proposing an alternative approach. Here we note some of the most serious errors in his criticism and inaccurate portrayals of DEA and SFA. Most of our attention is devoted to DEA, and to Stone's recommended alternative approach without much attention to SFA, partly because of his abbreviated discussion of the latter. In our response we attempt to be constructive as well as critical by showing how Stone's proposed approach can be joined to DEA to expand his proposal beyond limitations in his formulations.     

GDP指数随机化分析

指数是用于计算事物变动,特别是用于计算不可直接加总的现象之间综合变动情况的一种相对数,按照不同的划分标准,指数可以分为单指数、综合指数,或者质量指数、数量指数等。指数分析是统计学的一个重要的分析方法。一般的指数分析包括绝对数分析和相对数分析,相对数分析是分析综     

Bayesian local influence for survival models

The aim of this paper is to develop a Bayesian local influence method (Zhu et al. 2009, submitted) for assessing minor perturbations to the prior, the sampling distribution, and individual observations in survival analysis. We introduce a perturbation model to characterize simultaneous (or individual) perturbations to the data, the prior distribution, and the sampling distribution. We construct a Bayesian perturbation manifold to the perturbation model and calculate its associated geometric quantities including the metric tensor to characterize the intrinsic structure of the perturbation model (or perturbation scheme). We develop local influence measures based on several objective functions to quantify the degree of various perturbations to statistical models. We carry out several simulation studies and analyze two real data sets to illustrate our Bayesian local influence method in detecting influential observations, and for characterizing the sensitivity to the prior distribution and hazard function.     

Sample size calculation for logrank test and prediction of number of events over time

We review and compare existing methods for sample size calculation based on the logrank statistic and recommend the method of Lakatos for its accuracy and flexibility in allowing time-dependent rates of event, loss to follow-up, and noncompliance. We extend the Lakatos method to allow a general follow-up scheme, to handle non-inferiority tests, and to predict the number of events over calendar time. We apply the Lakatos method to the simple nonproportional hazard situation of delayed treatment effect to facilitate the comparison of different weighting methods and to evaluate the performance of the maximum combination tests. We use simulation studies to confirm the validity of the Lakatos method and its extensions.     

Reanalyzing Ultimatum Bargaining—Comparing Nondecreasing Curves Without Shape Constraints

We employ a hierarchical Bayesian method with exchangeable prior distributions to estimate and compare similar nondecreasing response curves. A Dirichlet process distribution is assigned to each of the response curves as a first stage prior. A second stage prior is then used to model the hyperparameters. We define parameters which will be used to compare the response curves. A Markov chain Monte Carlo method is applied to compute the resulting Bayesian estimates. To illustrate the methodology, we re-examine data from an experiment designed to test whether experimenter observation influences the ultimatum game. A major restriction of the original analysis was the shape constraint that the present technique allows us to greatly relax. We also consider independent priors and use Bayes factors to compare various models.     

多种综合评价方法的优劣判断研究

一、评价方法优劣判据的提出对于多指标多对象的综合评价 ,人们已提出许多不同的综合评价方法。传统评价方法有综合评分法、标准化计分法和功效系数法 ;多目标决策评价方法有优序法、引进次序法、双基点法和投影法 ;现代评价方法有主成分分析法 ,因子分析法、熵值法、模糊评价法、灰色关联分析评价法和层次分析评价法等。这些方法的应用相当活跃。但由于各种评价方法对原始数据的处理、权数的确定、评价方法本身掌握的标准和计算方法的不同 ,使评价结果存在着差异。这就向我们提出一个问题 ,即如何对各种综合评价方法进行优劣判断。我们认为…     

Calibrated imputation in surveys under a quasi-model-assisted approach

Summary.  We propose to use calibrated imputation to compensate for missing values. This technique consists of finding final imputed values that are as close as possible to preliminary imputed values and are calibrated to satisfy constraints. Preliminary imputed values, potentially justified by an imputation model, are obtained through deterministic single imputation. Using appropriate constraints, the resulting imputed estimator is asymptotically unbiased for estimation of linear population parameters such as domain totals. A quasi-model-assisted approach is considered in the sense that inferences do not depend on the validity of an imputation model and are made with respect to the sampling design and a non-response model. An imputation model may still be used to generate imputed values and thus to improve the efficiency of the imputed estimator. This approach has the characteristic of handling naturally the situation where more than one imputation method is used owing to missing values in the variables that are used to obtain imputed values. We use the Taylor linearization technique to obtain a variance estimator under a general non-response model. For the logistic non-response model, we show that ignoring the effect of estimating the non-response model parameters leads to overestimating the variance of the imputed estimator. In practice, the overestimation is expected to be moderate or even negligible, as shown in a simulation study.     

The long-term effectiveness of refusal conversion procedures on longitudinal surveys

Summary.  Survey organizations often attempt to 'convert' sample members who refuse to take part in a survey. Persuasive techniques are used in an effort to change the refusers' minds and to agree to an interview. This is done to improve the response rate and, possibly, to reduce non-response bias. However, refusal conversion attempts are expensive and must be justified. Previous studies of the effects of refusal conversion attempts are few and have been restricted to cross-sectional surveys. The criteria for 'success' of a refusal conversion attempt are different in a longitudinal survey, where for many purposes the researcher requires complete data over multiple waves. The paper uses data from the British Household Panel Survey from 1994 to 2003 to assess the long-term effectiveness of refusal conversion procedures in terms of sample sizes, sample composition and data quality.     

Fitting Emax models to clinical trial dose–response data when the high dose asymptote is ill defined

We consider fitting the so‐called Emax model to continuous response data from clinical trials designed to investigate the dose–response relationship for an experimental compound. When there is insufficient information in the data to estimate all of the parameters because of the high dose asymptote being ill defined, maximum likelihood estimation fails to converge. We explore the use of either bootstrap resampling or the profile likelihood to make inferences about effects and doses required to give a particular effect, using limits on the parameter values to obtain the value of the maximum likelihood when the high dose asymptote is ill defined. The results obtained show these approaches to be comparable with or better than some others that have been used when maximum likelihood estimation fails to converge and that the profile likelihood method outperforms the method of bootstrap resampling used. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

Estimating the hazard functions of two alternating recurrent events in the presence of covariates

The motivation for this paper is a cystic fibrosis data which records a patient’s times to relapse and times to cure under several recurrences of the disease. The idea is to study the impact of covariates on the hazard rates of two alternately occurring events. The dependence between the times to the two events over the different cycles is modeled through an autoregressive-type setup. The partial likelihood function is then derived and the estimators obtained. The estimators are shown to be consistent and asymptotically normal. The technique is applied to study the motivating data. A simulation study is also conducted to corroborate the results.