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。     

基于二阶段抽样的双重抽样框估计量设计

为了探究多阶段抽样情形下双重抽样框调查的估计量设计,文章对双重抽样框下的二阶段抽样估计方法进行了研究,得出了简单随机抽样下的总体总值估计及其估计量方差,对于更高阶段的抽样估计量设计,可以在二阶段的基础上扩展。文章所得的分析结果可为实际部门在双重抽样框下进行二阶段（或者多阶段）抽样调查提供相关的理论基础。     

基于多重抽样框的连续性抽样估计方法研究

多重抽样框可以解决单一抽样框难以完整覆盖流动性目标总体的难题,连续性抽样调查则可以获取变量的时序观测数据,对总体现象进行追踪调查。本文将多重抽样框调查与连续性抽样调查两种方法结合在一起进行研究,深入分析基于多重抽样框的连续性抽样估计方法。文章首先设计了连续性调查环境下总体结构变动表;然后,在简单随机抽样假定下的轮换样本调查情形开展研究,设计了14种参数缩减方法对构建的似然函数进行估计求解,并给出了估计量的迭代计算过程;最后,对本文的研究内容进行了总结与展望。     

基于多重抽样框的校准估计方法研究

在现代抽样调查中,校准估计方法能够通过有效利用辅助信息来提高估计量的精度,多重抽样框抽样调查则不仅可以解决单一抽样框覆盖不全的问题,还可以节约抽样设计阶段的成本。本文将这两种现代抽样估计与设计方法进行结合,将校准估计方法引入到基于多重抽样框的抽样调查体系中,在实现节约调查成本的同时,还能够提高估计量的精度。文章首先按照分离抽样框与组合抽样框估计方法的分类思路,对传统多重抽样框估计方法进行系统梳理;然后在最短距离法校准估计的分析框架下,按照调查时所能掌握辅助信息的具体情况,给出了两类多重抽样框估计情形下的各种不同形式的校准估计量;随后数值分析的比较结果也表明在多重抽样框中校准估计量的估计效率明显优于传统估计量;最后对本文研究进行总结的基础上,给出了我国抽样实践中应用这套先进抽样估计方法体系的展望。     

如何编好抽样框

抽样框是用来代表总体 ,从中抽选样本的一个框架。准确、完备的抽样框是开展抽样调查的前提条件。抽样框误差主要来自 :1.遗漏目标总体单位 ;2 .包含非目标总体单位 ;3.上述两种情况并存 ;4 .复合链接 ;5 .抽样框的陈旧 ;6 .辅助信息不正确。可以采取以下方法减少抽样框误差。首先 ,在抽选样本之前 ,要对抽样框加以检查 ,发现可能存在的问题 ,进行识别、处理 ,并采取一定措施加以补救。可以和普查或其他调查资料的总值或行政记录等相比较、分析 ,进而查明是否存在遗漏或去除已注销的单位。可以利用客观现实的相互联系 ,找出平衡关系 ,推算是…     

不完整抽样框的影响及补救的方法

建立科学的抽样框是抽样调查的基础和前提。不完整抽样框是抽样框误差中影响最为显著而且也是较难补救的一种。文章就不完整抽样框对调查估计量的影响以及补救的方法进行了探讨。     

中国“三农”抽样调查之抽样框问题研究

20世纪90年代后期,中国的＂三农＂问题逐步突显出来,涉及＂三农＂问题的抽样调查也越来越多。然而,抽取样本依据的抽样框大多是基于普查和行政记录资料编制的单纯名录抽样框。单纯名录抽样框的使用存在很多弊端。拟从抽样框的建立与更新维护两个阶段进行分析,提出解决现有问题的具体思路。在抽样框的建立阶段,建立名录抽样框和区域抽样框相结合的双重简单抽样框,并在此简单抽样框的基础上添加特征群,构建适合不同调查类别的复杂抽样框;在抽样框的更新维护阶段,通过合理地制度安排,以普查数据为基础,以建设抽样框数据库为契机开展抽样框的更新维护工作,使建成的抽样框得到及时有效地更新维护。     

抽样框缺陷及误差控制

文章阐述了几种主要的抽样框缺陷,并提出通过辅助信息、比估计、域估计等方法来补救这些缺陷.     

对丢失总体元素引起抽样框误差的研究

本文分两种情形利用模型对丢失总体元素引起的抽样效果影响进行了测定,并给出了具体的补救方法。     

抽样框误差测量及其控制

我国在抽样理论和方法中,对抽样框误差的讨论并不多,且涉及定量分析的内容更少。故对抽样框误差进行量化分析有着重要的意义。本文将比较全面地分析抽样框误差,定量测定其对估计量的影响,并提出相对有效的调整控制方法。     

Optimality Of Some Two-Stage Sampling Methods

Two-stage sampling plans in which the estimator is computed from the second sample only, and has a guaranteed precision irrespective of the parameter value, are considered. We prove the following optimality property for existing strategies in binomial and Poisson populations: there exists no other

strategy, of the same form, that guarantees the same precision, without increasing the expected sample size for some parameter valucs. The method of proof is illustrnted by proving a similar result for normal populations     

Two-Stage Cluster Sampling with Ranked Set Sampling in the Secondary Sampling Frame

Motivated by a real-life problem, we develop a Two-Stage Cluster Sampling with Ranked Set Sampling (TSCRSS) design in the second stage for which we derive an unbiased estimator of population mean and its variance. An unbiased estimator of the variance of mean estimator is also derived. It is proved that the TSCRSS is more efficient—in the sense of having smaller variance—than the conventional two-stage cluster simple random sampling in which the second-stage sampling is with replacement. Using a simulation study on a real-life population, we show that the TSCRSS is more efficient than the conventional two-stage cluster sampling when simple random sampling without replacement is used in both stages.     

Hypothesis Testing in Two-Stage Cluster Sampling

Correlated observations often arise in complex sampling schemes such as two-stage cluster sampling. The resulting observations from this sampling scheme usually exhibit certain positive intracluster correlation, as a result of which the standard statistical procedures for testing hypotheses concerning linear combinations of the parameters may lack some of the optimal properties that these possess when the data are uncorrelated. The aim of this paper is to present exact methods for testing these hypotheses by combining within and between cluster information much as in Zhou & Mathew (1993).     

A Class of Estimators Using Auxiliary Information in Two-Stage Sampling

This paper presents a general class of estimators for the finite population total when the emphasis is laid on the use of two auxiliary variables in a two-stage sampling.     

基于平衡单水平轮换的连续性抽样估计方法研究

内容提要：针对现存的各种单水平轮换模式和估计方法,本文提出一套统一的平衡单水平轮换模式。在此轮换模式下,引入两类相关关系,运用线性无偏估计方法,并通过使不同类型估计量方差的加权总和最小的方法确定最优系数,从而得到最优线性无偏估计量,不仅能够减少甚至消除估计量偏差的影响,还能使得连续性调查的整体抽样误差最小,适合估计各种类型的估计量。     

基于回归组合技术的连续性抽样估计方法研究

在使用样本轮换的连续性抽样调查中,不仅可以利用前期调查的研究变量的信息,还可使用现期调查的辅助变量信息来建立回归模型进行回归估计,进而构造回归组合估计量,并在此基础上确定最优样本轮换率和最优权重系数,使得回归组合估计量的方差最小,从而更大程度地提高连续性抽样调查的估计精度。     

Two-Stage Variables Acceptance Sampling Plans Using Process Loss Functions

In this article, a variable two-stage acceptance sampling plan is developed when the quality characteristic is evaluated through a process loss function. The plan parameters of the proposed plan are determined by using the two-point approach and tabulated according to various quality levels. Two cases are discussed when the process mean lies at the target value and when it does not, respectively. Extensive tables are provided for both cases and the results are explained with examples. The advantage of the proposed plan is compared with the existing variable single acceptance sampling plan using the process loss function.     

Two-Stage Estimation in Copula Models Used in Family Studies

In this paper register based family studies provide the motivation for studying a two-stage estimation procedure in copula models for multivariate failure time data. The asymptotic properties of the estimators in both parametric and semi-parametric models are derived, generalising the approach by Shih and Louis (Biometrics vol. 51, pp. 1384–1399, 1995b) and Glidden (Lifetime Data Analysis vol. 6, pp. 141–156, 2000). Because register based family studies often involve very large cohorts a method for analysing a sampled cohort is also derived together with the asymptotic properties of the estimators. The proposed methods are studied in simulations and the estimators are found to be highly efficient. Finally, the methods are applied to a study of mortality in twins.