多指标抽样的样本容量设计方法

在抽样调查中,首先必须确定样本容量.样本容量既取决于调查费用,同时也受估计精度的制约.多指标抽样是一种常用而复杂的调查方法.样本容量的确定就成了多指标抽样设计的难点.文章首先在理论上阐明最优样本容量的存在;然后介绍了确定样本容量的一般方法;在此基础上,分两种情况对多指标抽样背景下样本容量设计进行了详细讨论.     

规模以下工业抽样设计研究

为推动规模以下工业抽样调查工作以及解决当前调查面临的有关问题,本文对抽样设计进行了改进研究。首先,本文对规模以下工业抽样设计演变过程进行系统梳理,总结了现行抽样设计充分利用双重抽样框设计和综合运用三种抽样方法的特点。其次,针对园区层企业密度高的特点,探索结合园区因素改进地域抽样设计,对园区层和非园区层分别抽样,解决调查中面临的非抽样误差问题,并调整辅助变量使其与核心指标相关性均较高,确保抽样推断精度,有效提高抽样调查效率。并以我国东 部某省为例进行实证模拟得到结合园区因素抽样设计对调查工作改进的结论。再次,针对我国各级政府管理需要以及局队业务分工优化调整情况,介绍了规模以下工业样本追加理论和实证应用的主要研究成果。最后,在大数据时代数据来源广泛的背景下,本文在多重抽样框设计以及利用辅助变量提升样本轮换推断精度方面提出了进一步改进抽样设计的思路。     

推行“MPPS”，促进农村统计工作上新台阶

“MPPS”即多目标与规模成比例的概率抽样。它是在“PPS”即与规模成比例的概率抽样的基础上,考虑了多种调查目标的因素抽取调查样本,以满足多种调查指标的需要。目前,广东已制定出《广东省农村统计多目标复合抽样调查方案》。该方案省市县三级样本兼容、多目标调查,能够满足多级政府管理、调查指标多样化的需要,是一种适合当前经济管理体制、满足统计调查目标需要的较为理想的抽样调查方法。 随着市场经济发展的不断深入,对农村统计的要求越来越高。从原来以产品产量为主,转变为以农产品价格、农业经济核算、农业生产投入和农民收入支出等指标为主。党的“十六”大提出全面建设小康社会的宏伟目标后,农村统计工作更要为建设小康社会服务,必须建立科学的小康监测指标。农民收入支出、农产品价格、农业生产投入等等靠全面报表方法收集统计数据,在目前的经济体制下是不可能做到的。只     

MPPS抽样设计方差估计的比较研究

一、引言1997年,美国农业部国家农业统计署(NASS)专家Jeffrey T.Bailey和Phillip Kott[1]提出MPPS抽样方法,用于解决多目标抽样问题,即:在有限的资源条件下,为得到多个目标变量的值,如果按单个目标进行抽样,对数据和信息的需求使得调查次数和(或)调查内容增加,从而无法体现抽样调查高效与灵活的优点;MPPS方法采用了多变量与抽样单元规模成比例的概率抽样,实现了多目标抽样。以全国性的农业抽样调查为例,其抽样方案常涉及多阶抽样。其中以二阶抽样为例,第一阶抽取行政村,第二阶抽取农户。许多国家经常使用的方法是,第一阶抽样用分层与…     

迭代方法在多目标总体抽样调查中的应用

一、问题的提出在抽样调查实践中经常会遇到多目标抽样问题 ,包括多目标变量问题和多目标总体问题。多目标变量问题 ,是指用一套样本估计多个目标变量的总量、均值、比率和比例等估计量时 ,由于各个变量的总体分布不一致 ,导致不同变量的估计量精度 (一般用相对误差表示 )不同 ,而且可能相差很大。在实践中 ,多目标变量问题是一个普遍问题 ,因为任何一项调查都不可能仅仅调查一个指标 (即变量 )。解决多目标变量问题的关键是在抽样设计中选择合适的辅助变量。一般来说 ,在抽样设计中作为分层辅助信息的变量的估计量精度会比其他变量的估计量…     

抽样调查中的相对误差及其替代指标─—构造一种新的适合多目标抽样的误差比较和控制指标

相对误差在抽样误差的控制中以及抽样设计方案效果的评估与比较中都有重要作用。但是相对误差的作用主要局限于单目标抽样中,对于多目标抽样,相对误差不能继续发挥其在单目标抽样中的作用。而且,即使在单目标抽样中,相对误差有时也会出现问题,不能发挥应有的作用。因此,需要对相对误差指标进行改造,以适应实际需要。目前以及今后相当长的一段时间里,多目标抽样都将作为一种很重要抽样方法在我国得到推广、普及。因此,本文讨论的问题具有重要的现实意义。一抽样调查中相对误差的作用据经验及统计文献的记述,相对误差的作用有三种：…     

抽样调查实施中的不规范性

一、不规范性的种种表现　　首先 ,从抽样设计角度分析。抽样设计是针对抽样调查全过程所作的通盘考虑和整体安排 ,包括抽样调查要求方面的设计、调查内容方面的设计、抽样与推断的技术方法方面的设计、以及有关调查组织工作方面的设计等。从某种意义上讲 ,抽样设计的质量好坏 ,直接决定着抽样调查的成败。在这方面存在的主要问题是 :①不重视抽样框的建立 ,对有缺陷的抽样框既不作有效的调整 ,也不作任何说明。众所周知 ,抽样框是赖以实施概率抽样的基本依据 ,从一个完备的抽样框出发 ,就有可能得到一个对总体具有代表性的样本 ,而从一个存…     

几种抽样推断方式的比较

抽样调查从方法论来讲,有两个基本问题:一是如何从总体中选取部分单位,即抽样方式;二是如何根据部分单位的调查结果来推断总体结果,即推断方式。推断方式有:均值推断,比率推断,回归推断。抽样推断方式的选用,不仅是个理论问题,也是一个实际工作中经常碰到的问题,如农产量抽样调查中,究竟采用哪种推断方式为好,各地作过一些试算,但意见不一。本文主要从抽样理论的角度,来阐明各种推断方式的优良性,并作比较研究。(一)均值推断:用样本调查指标的均值直接作为总体指标均值的估计,就是均值     

总体分高低成本下的复合多目标抽样方案的设计与应用

文章依据复合多目标抽样的基本原理,提出了高低成本指标广义相关下的多目标复合抽样方法的设计方案,探讨了依广义相关性进行分类的抽样方案在精度和成本方面的优良性,并进行了实际比较与应用。     

高低成本指标广义相关下的多目标复合抽样方法的设计与应用

文章依据复合多目标抽样基本原理,提出了高低成本指标广义相关下的多目标复合抽样方法的设计方案;探讨了依广义相关性进行分类的抽样方案在精度和成本方面的优良性,并进行了实际比较与应用。     

Randomized response techniques: An application to the Botswana AIDS impact survey

The performance of the sampling strategy used in the Botswana Aids Impact Survey II (BAISII) has been studied in detail under a randomized response technique. We have shown that alternative strategies based on the Rao–Harley–Cochran (RHC) sampling scheme for the selection of first stage units perform much better than other strategies. In particular, the combination RHC for the selection of first stage units (fsu's) and systematic sampling for the selection of second stage units (ssu's) perform the best when the sample size is small where as the RHC and SRSWOR perform the best when the sample size is large. In view of the present findings it is recommended that the BAISII survey should be studied in more detail incorporating more indicators and increased sample sizes. This is because the BAISII survey design is extensively in use for large scales surveys in Southern African countries.     

概率抽样条件下样本代表性事后评估方法探讨

 样本代表性直接牵扯到统计数据质量和统计公布引起的民众反响,目前社会上不乏对政府统计数据的质疑之声,最终影响到政府统计机关的公信力,因此有必要重新审视现行样本代表性的研究。目前相关文献普遍强调不同抽样方式下的样本代表性的相对性内涵,确保样本的代表性仅从抽样方法和样本量两个维度入手,缺乏对既定抽样方法下样本代表性的事后评估体系的探索,以及多样本之间样本代表性优劣的比较方法研究。鉴于此,本文在结合人口普查数据基础上尝试从样本-总体整体分布和内部属性结构两个方面构建样本代表性事后评估的一整套指标和假设检验,进而找到一种多样本代表性比较的依据。最后对浦东新区2010年城镇居民收入调查样本进行了代表性检验的尝试。     

ON TWO-STAGE SUCCESSIVE SAMPLING

In repeated sampling enquiries application of method of successive sampling with partial replacement of units is advantageous. In this paper use of successive sampling technique when the sampling design is multi-stage has been studied. Estimates of population mean and its variance have been obtained (a) on the second occasion, and (b) on the h-th occasion under two systems of replacement, namely (i) by retaining only a fraction p of psu's along with their sample of ssu's, and (ii) by retaining all the psu's on the second occasion, but from each psu only a fraction p of the ssu's within them is retained. A cost function suitable to the design has been illustrated, with the help of data collected from a sample survey conducted by the Indian Council of Agricultural Research.     

On the Problem of Compromise Allocation in Multi-Response Stratified Sample Surveys

In stratified sample surveys, the problem of determining the optimum allocation is well known due to articles published in 1923 by Tschuprow and in 1934 by Neyman. The articles suggest the optimum sample sizes to be selected from each stratum for which sampling variance of the estimator is minimum for fixed total cost of the survey or the cost is minimum for a fixed precision of the estimator. If in a sample survey more than one characteristic is to be measured on each selected unit of the sample, that is, the survey is a multi-response survey, then the problem of determining the optimum sample sizes to various strata becomes more complex because of the non-availability of a single optimality criterion that suits all the characteristics. Many authors discussed compromise criterion that provides a compromise allocation, which is optimum for all characteristics, at least in some sense. Almost all of these authors worked out the compromise allocation by minimizing some function of the sampling variances of the estimators under a single cost constraint. A serious objection to this approach is that the variances are not unit free so that minimizing any function of variances may not be an appropriate objective to obtain a compromise allocation. This fact suggests the use of coefficient of variations instead of variances. In the present article, the problem of compromise allocation is formulated as a multi-objective non-linear programming problem. By linearizing the non-linear objective functions at their individual optima, the problem is approximated to an integer linear programming problem. Goal programming technique is then used to obtain a solution to the approximated problem.     

Embedded experiments in repeated and overlapping surveys

Summary.  Statistical agencies make changes to the data collection methodology of their surveys to improve the quality of the data collected or to improve the efficiency with which they are collected. For reasons of cost it may not be possible to estimate the effect of such a change on survey estimates or response rates reliably, without conducting an experiment that is embedded in the survey which involves enumerating some respondents by using the new method and some under the existing method. Embedded experiments are often designed for repeated and overlapping surveys; however, previous methods use sample data from only one occasion. The paper focuses on estimating the effect of a methodological change on estimates in the case of repeated surveys with overlapping samples from several occasions. Efficient design of an embedded experiment that covers more than one time point is also mentioned. All inference is unbiased over an assumed measurement model, the experimental design and the complex sample design. Other benefits of the approach proposed include the following: it exploits the correlation between the samples on each occasion to improve estimates of treatment effects; treatment effects are allowed to vary over time; it is robust against incorrectly rejecting the null hypothesis of no treatment effect; it allows a wide set of alternative experimental designs. This paper applies the methodology proposed to the Australian Labour Force Survey to measure the effect of replacing pen-and-paper interviewing with computer-assisted interviewing. This application considered alternative experimental designs in terms of their statistical efficiency and their risks to maintaining a consistent series. The approach proposed is significantly more efficient than using only 1 month of sample data in estimation.     

Variance estimation in complex survey sampling for generalized linear models

Summary.  Complex survey sampling is often used to sample a fraction of a large finite population. In general, the survey is conducted so that each unit (e.g. subject) in the sample has a different probability of being selected into the sample. For generalizability of the sample to the population, both the design and the probability of being selected into the sample must be incorporated in the analysis. In this paper we focus on non-standard regression models for complex survey data. In our motivating example, which is based on data from the Medical Expenditure Panel Survey, the outcome variable is the subject's 'total health care expenditures in the year 2002'. Previous analyses of medical cost data suggest that the variance is approximately equal to the mean raised to the power of 1.5, which is a non-standard variance function. Currently, the regression parameters for this model cannot be easily estimated in standard statistical software packages. We propose a simple two-step method to obtain consistent regression parameter and variance estimates; the method proposed can be implemented within any standard sample survey package. The approach is applicable to complex sample surveys with any number of stages.     

基于双重抽样框的抽样估计方法研究

 随着经济社会的快速发展,抽样调查中调查对象的流动日益频繁,传统的单一抽样框很难完整覆盖流动性的目标总体,如果一定要使单一抽样框实现完整覆盖,成本必定是高昂的,甚至由于编制过程漫长使抽样调查失去其时效性。有时采用两个不完整抽样框的组合可以实现对目标总体的完整覆盖。基于双重抽样框进行抽样调查,其抽样设计工作不难,但是由于样本在两个抽样框中存在交叉,致使抽样估计甚是困难。基于此,本文将系统评述目前国外已有的各种双重抽样框估计方法,将这些方法分为分离抽样框估计和组合抽样框估计两类,并按照统一的模式比较各估计方法的功效,文章最后对我国采用双重抽样框调查进行展望。     

人口变动情况抽样调查的抽样误差分析

人口变动情况抽样调查是我国获得年度人口数据的主要渠道之一,自１９８３年以来已进行了１５次。１９８３—１９８８年样本量的设计只对全国有较好的代表性,为了保证人口变动情况抽样调查的主要指标对全国和各省、自治区、直辖市有较好的代表性,自１９８９年开始人口变...     

关于多维指标抽样调查中删除指标的均值估计

针对多维度指标抽样调查情况,运用多变量幂函数逼近理论,对多指标中删除的指标构造出一类依赖于保留指标的估计量,通过对其性质的讨论,得出了该估计量的抽样误差与样本量的倒数同阶的结论。在抽样调查的实际应用中,可以根据给定的抽样误差,对部分指标进行调查,未被调查指标的均值通过调查指标值的估计去实现,从而达到了解全部指标信息的目的。