《统计研究》与我国抽样调查理论及实践的发展

在《统计研究》复刊之初,《统计研究》就在1985年分几期连载了现代抽样技术介绍,系统地向我国统计学界介绍了现代抽样调查的理论和方法,为现代抽样调查理论和方法在我国的传播起到了推动作用。随着我国统计学界对现代抽样调查理论与方法的了解和掌握,我国统计学界对抽样调查理论与方法的研究也日趋活跃,而《统计研究》则成了我国抽样调查理论与方法研究成果发表的一个重要阵地。十几年来,围绕着我国抽样调查实践活动中遇到的各种问题,《统计研究》发表了一系列的理论探讨文章。在这些文章中,探讨的主题主要有:(1)多目标抽样的方法和分层技术…     

贸易统计方法制度改革之我见——现行贸易企业抽样调查存在的问题与思考

对小型和个体批发零售贸易、餐饮业进行抽样调查统计(以下简称贸易统计),已实行多年,这种方法运用效果较好,但运行中仍存在一些问题,还不能完全满足分级管理的需要,受多种因素的制约,统计数据质量不高,需要进一步改进和完善现行贸易统计制度方法。 一、贸易统计存在的问题 (一)现行贸易统计抽样调查中分级管理需要存在的问题 1、目前,贸易抽样调查方案,采取分层抽样调查方法,以盟市级为     

空间分层数据无条件模型的改进及其估计

抽样调查中得到的数据经常既包含个体信息又包含地理单元信息,形成以地区集聚的分层数据.空间分层数据中地理单元间往往具有空间依赖性,区别于传统的分层数据.分析空间分层数据时需要首先建立无条件模型用作初步分析.因此,在传统分层无条件模型中引入完全空间自回归模型来表达空间相关性,建立空间分层数据的无条件模型,并研究其估计方法,借助参数估计值可做模型选择.     

多目标抽样调查技术研究

一、多目标抽样调查技术研究的意义和任务 众所周知,对于一个总体,通过抽样调查估计其一个指标并不是件困难的事,只需要对抽样框做合理的分层（以降低层内差异）,再进行科学的选样（即不违背随机原则）,最后由样本统计量计算出来的估计值对总体参数的     

基于分层贝叶斯分析的残疾率小域估计方法

小域估计（Small Area Estimation）是抽样调查领域里一个重要的研究方向,国计民生中的许多重要问题如失业率、传染病的发病率和民意测验等抽样调查都需要采用不同的小域估计方法。本文针对小域估计问题,以估计方法发展脉络为主线,以分层贝叶斯分析的小域估计为重点,对小域估计问题的理论、方法和最新进展进行简述,并利用澳大利亚残疾、老龄化和护理者（SDAC 2003）抽样调查实际数据,从分层贝叶斯分析角度对澳大利亚残疾率进行估计,最后对估计结果进行比较和讨论。     

我国政府统计抽样调查的回顾与思考

随着我国经济社会的快速发展和统计体制改革的不断推进,抽样调查在我国政府统计中得到越来越广泛的应用,抽样调查在统计调查方法体系中的主体地位也日益凸显,抽样调查的理论和应用都有了长足发展。然而,随着改革的不断深入和现代化进程的加速,我国的抽样调查所面临的问题也随之出现,抽样调查所面临的新的制约因素也不断出现,需要亟待解决。一、历史回顾1949年以前,抽样调查在我国的应用很少,有关抽样理论与方法的研究也不多     

对完善,推广抽样调查的几点认识

随着抽样理论的日趋完善,抽样调查技术在世界范围内的各个领域都得到了广泛应用和发展。在我国,过去由于实行计划经济体制,搜集统计资料主要依靠全面统计报表,对抽样调查的理论研究较少,应用也局限于少数领域。实行改革开放以来,抽样调查在我国很多领域得到了推广应用,但与一些先进国家相比,无论是理论研究,还是抽样技术及应用水平都还存在着一定差距。为此,如何进一步完善与推广抽样调查已成为统计理论和实践的重要课题。一、抽样调查的特点和优越性在众多的统计调查方法中,抽样调查是一种有着独特特点和优越性的调查方法,它是…     

本期导读

人口普查事后质量抽查属于大规模抽样调查,是世界各国在人口普查中普遍采取的用来评估人口普查登记质量的调查方法.是评价数据质量的重要手段之一.<人口普查事后质量抽查的事后分层估计初探>一文,在讨论抽样调查分层原理的基础上,分析了人口普查事后质量抽查的事后分层的标志选择和层数确定.并对事后分层双系统估计量及人口普查总体真实人口数事后分层估计方法进行了探讨.     

浅谈永久随机数技术在抽样调查实践中的应用

永久随机数（Permanent Random NumbersPRNs）技术在各国的抽样调查实践中有着广泛的应用。近年来，我国抽样调查领域也开始引入永久随机数法抽样技术，如规模以下工业抽样调查等。本文根据本人近年来在规模以下工业抽样调查学习和实践中的一些体会，介绍永久随机数法抽样技术的几种应用，希望能够为其它专业的抽样调查实践提供一些参考和借鉴作用，以促进永久随机数法抽样技术在统计调查中的应用和推广。     

在统计实际工作中要科学运用抽样调查方法

近年来抽样调查的应用有了很大的发展。在抽样调查中，样本抽取方法多数基层统计机构均采用了概率抽样方法来获取样本，其中使用量多的有分层多阶抽样（包括整群抽样）、分层多阶不等概率（特别是与单元大小成比例、即pps）抽样、各种系统（等距）抽样，包括按有关标识排队的系统抽样，对称系统抽样与PPS系统抽样等。但在实际应用方面也显现出不少问题。如果我们不重视这些问题，将成为今后经济的发展与统计工作的严重障碍。     

Group Testing,the Pooled Hypergeometric Distribution,and Estimating the Number of Defectives in Small Populations

The testing of combined bacteriological samples – or “group testing” – was introduced to reduce the cost of identifying defective individuals in populations containing small proportions of defectives. It may also be applied to plants, animals, or food samples to estimate proportions infected, or to accept or reject populations. Given the proportion defective in the population, the number of positive combined samples is approximately binomial when the population is large: we find the exact distribution when groups include the same number of samples. We derive some properties of this distribution, and consider maximum-likelihood and Bayesian estimation of the number defective.     

Parameter estimation for ihe birnbaum-saunders distribution based on symmetrically censored samples

Ihe Bimbaum-Saunders distribution was derived to model fatigue life. Frequently, it becomes necessary to stop a life testing process before all the test items have failed. Therefore, estimation procedures need to be developed for use when censoring occurs. In this article, we have derived estimators for the parameters of this distribution which may be used for complete samples or Type II symmetrically censored samples A simulation study was also conducted to examine the performance of these estimators.     

Estimated Data Collection Organization Effect in the National Medical Care Expenditure Survey

The National Medical Care Expenditure Survey, which has a complex survey design, is further complicated by combining two independently drawn national samples of households from the Research Triangle Institute (RTI) and the National Opinion Research Center (NORC). It is assumed that since the structures of these national-area samples are similar, they are thereby compatible and allow for the derivation of statistically equivalent unbiased national estimates of relevant health parameters. In this paper, national parameter estimates of relevant demographic and health measures were separately produced for each of the two survey organizations and a determination was made regarding statistical equivalence across samples. In addition, the data-collection organization effect was estimated and tested within the framework of a multivariate analysis appropriate for complex survey data. The findings consistently revealed a statistically nonsignificant data-collection organization effect when testing for differences in domain estimates of the relevant health parameters under consideration.     

A comparison of models for clustered binary outcomes: analysis of a designed immunology experiment

The lymphocyte proliferative assay (LPA) of immune competence was conducted on 52 subjects, with up to 36 processing conditions per subject, to evaluate whether samples could be shipped or stored overnight, rather than being processed on fresh blood as currently required. The LPA study resulted in clustered binary data, with both cluster level and cluster-varying covariates. Two modelling strategies for the analysis of such clustered binary data are through the cluster-specific and population-averaged approaches. Whereas most research in this area has focused on the analysis of matched pairs data, in many situations, such as the LPA study, cluster sizes are naturally larger. Through considerations of interpretation and efficiency of these models when applied to large clusters, the mixed effect cluster-specific model was selected as most appropriate for the analysis of the LPA data. The model confirmed that the LPA response is significantly impaired in individuals infected with the human immunodeficiency virus (HIV). The LPA response was found to be significantly lower for shipped and overnight samples than for fresh samples, and this effect was significantly stronger among HIV-infected individuals. Surprisingly, an anticoagulant effect was not detected.     

Assessing convergence diagnostic tests for Bayesian Cox regression

The Markov chain Monte Carlo (MCMC) method generates samples from the posterior distribution and uses these samples to approximate expectations of quantities of interest. For the process, researchers have to decide whether the Markov chain has reached the desired posterior distribution. Using convergence diagnostic tests are very important to decide whether the Markov chain has reached the target distribution. Our interest in this study was to compare the performances of convergence diagnostic tests for all parameters of Bayesian Cox regression model with different number of iterations by using a simulation and a real lung cancer dataset.     

A Monte Carlo comparison of three consistent bootstrap procedures

Since bootstrap samples are simple random samples with replacement from the original sample, the information content of some bootstrap samples can be very low. To avoid this fact, several variants of the classical bootstrap have been proposed. In this paper, we consider two of them: the sequential or Poisson bootstrap and the reduced bootstrap. Both of these, like the ordinary bootstrap, can yield second-order accurate distribution estimators, that is, the three bootstrap procedures are asymptotically equivalent. The question that naturally arises is which of them should be used in a practical situation, in other words, which of them should be used for finite sample sizes. To try to answer this question, we have carried out a simulation study. Although no method was found to exhibit best performance in all the considered situations, some recommendations are given.     

A perspective of composite sampling

Composite samples are formed by physically mixing samples. Usually, composite samples are used to reduce the overall cost associated with analytical procedures that must be performed on each sample, but they can also be used to protect the privacy of individuals.

Composite sampling can reduce the cost of identifying individual cases that have a certain trait, such as those with a rare disease or those exceeding pollution-level standards. Not much is lost by applying this method as long as the trait is relatively rare.

Composite sampling can reduce the cost of estimating the mean of some process. When samples are composited, the ability to estimate the variance is lost. In spite of this, the potential savings are so great that composite samples have been used.

Much of this paper deasl with the variance of estimators based on composite sampling when the porportions of hte original samples comprising the composite sample are actually random. Taking repeated samples and measurements on several composite samples complicates the prodcedure, but allows the estimation of between and within variation as well as measurement error.     

A Generalized Distance Multi-Sample Test of Normality With Applications to Process Control

In statistical process control one typically takes periodic small samples. Statistical inferences made from these samples often assume that the samples come from normal distributions with the means and variances possibly changing over time. A multisample test of normality is proposed to test this assumption. The test statistic is the generalized distance between the standardized order statistic vector averaged across the samples and its expected value under normality. The null distribution of the statistic approaches a chi-squared distribution as the number of samples increases. A Monte Carlo study suggests that the test has desirable power properties relative to competing tests.     

Empirical Bayes estimation in continuous one-parameter exponential families under associated samples

In this paper, we study the empirical Bayes (EB) estimation in continuous one-parameter exponential families under negatively associated (NA) samples and positively associated (PA) samples. Under certain regularity conditions, it is shown that the convergence rates of proposed EB estimators under NA or PA samples are the same as those of EB estimators under independent observations, which significantly improve the existing results in EB estimation under associated samples.     

Fisher Information in Type II Progressive Censored Samples

Recently, progressively Type II censored samples have attracted attention in the study and analysis of life-testing data. Here we propose an indirect approach for computing the Fisher information (FI) in progressively Type II censored samples that simplifies the calculations. Some recurrence relations for the FI in progressively Type II censored samples are derived that facilitate the FI computation using the proposed decomposition. This paper presents a standard recurrence relation that simplifies computation of the FI in progressively Type II censored samples to a sum; FI in collections order statistics (OS). We compute the FI in a collections of progressively Type II censored samples for some known distributions.