抽样调查中样本不响应问题研究

抽样调查就是按照随机性原则．从总体中抽取部分单位进行调查,并通过对这部分单位的数据分析,给出总体数量特征具有一定可靠性的判断。可见,样本数据的全面性、系统性、准确性是抽样调查质量高低的关键。但是,在实际抽样调查中,经常会出现样本不响应。样本不响应的成因、后果及防范,在我国统计理论界和统计实践中都没有给予足够的重视。本文仅就样本不响应的种类、成因、后果及防范作一简单论述。 一、样本不响应的种类和成因 所谓不响应样本就是无法得到被选作样本单元的相关资料的样本。通常有样本单元不响应和样本项目不响应两类。…     

季度调查的一种两层次样本轮换方法

对于采用两阶段抽样设计的季度调查,构造了一种两层次样本轮换方法:一级单元的样本轮换模式为12in;二级单元的样本轮换模式为6in.从而保证了相邻两个季度之间二级单元的样本拼配率恒为5/6,还保证了相邻两年的相同季度之间二级单元的样本拼配率恒为1/3,更保证了一级单元的样本量在轮换过程中始终不变.由此可见,样本轮换方法可以应用于中国劳动力的调查中.     

浅谈城市住户调查样本轮换

我国城市住户调查从 1990年起实行样本轮换制 ,迄今已有十年的时间 ,期间有不少统计工作者或专家从理论到具体实施方面发表过自己的见解 ,提出诸多改进意见。本文拟就城市住户调查样本轮换中涉及的问题从理论角度提出自己的一点看法。一、样本轮换的原因对于我国城市住户调查进行样本轮换的原因 ,笔者认为可以归结为以下几点 :(一 )样本轮换是由其调查目的决定的。城市住户调查是一项以城市住户为对象 ,以搜集城市居民家庭社会经济统计资料为目的的综合性社会调查。通过调查 ,了解城市居民家庭人口、就业、收入、消费、储蓄、商品需求、住房…     

住户追踪调查中的样本维护策略

对一个大型的追踪调查来说,长期的追踪调查增加调查对象的回答负担,样本老化、样本流失等导致追踪样本不能很好地反映调查总体的变化特征,有效的样本维护策略是十分重要的。文章在介绍了追踪调查的优缺点基础上,主要对住户追踪调查的追踪规则,住户追踪调查中的一些维护策略,包含影响样本维护的因素、常规和非常规的样本维护措施进行探讨。     

改进样本代表性的多目标追加平衡设计

本文主要讨论样本代表性的改进和多目标调查两个问题。一,本文提出了一种新的改进样本代表性多目标抽样方法,增加样本量与调整样本结构相结合的方法-追加样本的平衡设计,即通过追加样本,使得补充的样本与原来的样本组合生成新的平衡样本,相对于初始样本,减少样本与总体的结构性偏差。平衡样本是指辅助变量总量的霍维茨汤普森估计量等于总体总量真值。二,平衡样本通过选择与多个目标参数相关的辅助变量,使得一套样本对不同的目标参数而言都具有良好的代表性,进而完成多目标调查。结合2010年第六次人口分县普查数据,通过选择多个目标参数,对追加样本后的平衡样本作事后评估结果表明,追加平衡设计能够有效改进样本结构,使得样本结构与总体结构相近,降低目标估计的误差;同时也说明平衡抽样设计能够实现多目标调查,提高样本的使用效率。     

住户调查样本选择及数据误差问题探讨

住户调查的样本选择是数据搜集是否可行与数据是否准确的关键。在我国,无论是城市住户调查,还是农村住户调查的样本选择都存在着直接导致数据偏差的因素,国际上的住户调查也普遍存在相似的问题。文章在分析住户调查中样本选择存在的问题及成因的基础上,指出为解决调查结果的误差,修正方法的应用是必然的选择。     

样本轮换在劳动工资抽样调查中的应用探讨

针对目前我国劳动工资抽样调查中存在长期样本不轮换而导致劳动工资数据与实际不符的情况,在借鉴国内外样本轮换技术应用实践和经验的基础上,结合上海劳动工资季度调查的实际情况,初步构造了劳动工资抽样调查中的子样本轮换方法,并指出了劳动工资抽样调查进一步改进的方向.     

对民意测验中不稳定样本的检验

在民意测验中,影响样本的代表性主要有两个因素:样本容量与样本单位的可信度。扩大样本容量与部分样本轮换可以保证样本的稳定性与可靠性,而保证样本单位的可信度一般要通过激励的方式。事实上对于部分样本单位存在激励无效的情形,一般采用部分重复抽样的方法来检验其可信度。如果以t检验证明其是小概率事件,就作为不稳定样本剔除。文章给出了一种检验不稳定样本的方法,表明其对民意测验结果的决定性影响和作用。     

中国劳动力调查样本轮换方法的新改进

中国劳动力调查采用的两层次样本轮换方法不能使得村级单元的样本量在轮换过程中保持恒定不变,因而需要改进。文章在笔者先前提出的改进方法的基础上,对劳动力调查样本轮换方法作了进一步改进。在新的改进方法中,村级单元的轮换模式为16in,小区的轮换模式为8in。     

轮换样本调查的轮换模式设计与估计方法

文章以我国城市住户调查的轮换模式设计为例,研究了轮换样本调查中的轮换模式设计与估计方法等问题.不完全单水平轮换模式是轮换样本调查中非常理想的一种轮换模式,既吸收了单水平轮换模式的优点,又充分体现了轮换样本调查的优势.文章所研究的这套轮换模式设计与估计方法不仅适合在我国城市住户抽样调查中使用,而且也可推广应用到我国政府统计部门开展的其他类型的连续性抽样调查中.     

Optimization of a product performance using mixture experiments

This article presents a case study of a chemical compound acting as a subsystem of a delay mechanism for starting a rocket engine. The objective of this study was to investigate the proportions of mix components that enable a previously specified burning time. Thus, a linear regression model with normal responses was fitted, but later considered inadequate, as there was evidence that the response variance was not constant. Models fitted by the quasi-likelihood method were tried then. Through the developed model, it was possible to determine the proportion of each component to accomplish the process optimization. For the process optimization, besides considering a specific burning time, it was possible to consider the variance minimization for this time prediction as well.     

A structured framework for assessing sensitivity to missing data assumptions in longitudinal clinical trials

The objective of this research was to demonstrate a framework for drawing inference from sensitivity analyses of incomplete longitudinal clinical trial data via a re‐analysis of data from a confirmatory clinical trial in depression. A likelihood‐based approach that assumed missing at random (MAR) was the primary analysis. Robustness to departure from MAR was assessed by comparing the primary result to those from a series of analyses that employed varying missing not at random (MNAR) assumptions (selection models, pattern mixture models and shared parameter models) and to MAR methods that used inclusive models. The key sensitivity analysis used multiple imputation assuming that after dropout the trajectory of drug‐treated patients was that of placebo treated patients with a similar outcome history (placebo multiple imputation). This result was used as the worst reasonable case to define the lower limit of plausible values for the treatment contrast. The endpoint contrast from the primary analysis was ? 2.79 (p = .013). In placebo multiple imputation, the result was ? 2.17. Results from the other sensitivity analyses ranged from ? 2.21 to ? 3.87 and were symmetrically distributed around the primary result. Hence, no clear evidence of bias from missing not at random data was found. In the worst reasonable case scenario, the treatment effect was 80% of the magnitude of the primary result. Therefore, it was concluded that a treatment effect existed. The structured sensitivity framework of using a worst reasonable case result based on a controlled imputation approach with transparent and debatable assumptions supplemented a series of plausible alternative models under varying assumptions was useful in this specific situation and holds promise as a generally useful framework. Copyright © 2012 John Wiley & Sons, Ltd.     

Sampling issues in the administration of justice

Colin Aitken first became interested in sampling in the context of the administration of justice when the case of US versus Shonubi was brought to his attention. Shonubi was a Nigerian working in New York. He was arrested at Kennedy Airport when seen behaving in a suspicious manner in the baggage hall, having returned on a flight from Nigeria. He was found to have 103 bags of a white substance inside him, four of which were examined. The white substance was identified as heroin. Shonubi was arrested, tried and found guilty of drug smuggling. The question then arose as to the length of sentence he should be given.     

The Clustering of Categorical Data: A Comparison of a Model-based and a Distance-based Approach

For clustering multivariate categorical data, a latent class model-based approach (LCC) with local independence is compared with a distance-based approach, namely partitioning around medoids (PAM). A comprehensive simulation study was evaluated by both a model-based as well as a distance-based criterion. LCC was better according to the model-based criterion and PAM was sometimes better according to the distance-based criterion. However, LCC had an overall good and sometimes better distance-based performance as PAM, although this was not the case in a real data set on tribal art items.     

Bayesian Fourier clustering of gene expression data

Clustering gene expression data are an important step in providing information to biologists. A Bayesian clustering procedure using Fourier series with a Dirichlet process prior for clusters was developed. As an optimal computational tool for this Bayesian approach, Gibbs sampling of a normal mixture with a Dirichlet process was implemented to calculate the posterior probabilities when the number of clusters was unknown. Monte Carlo study results showed that the model was useful for suitable clustering. The proposed method was applied to the budding yeast Saccaromyces cerevisiae and provided biologically interpretable results.     

Elite players’ perceptions of football playing surfaces: a mixed effects ordinal logistic regression model of players’ perceptions

The aim of this study was to determine potential explanatory factors that may be associated with different attitudes amongst the global population of elite footballers to the use of different surfaces for football. A questionnaire was used to capture elite football players’ perceptions of playing surfaces and a mixed effects ordinal logistic regression model was used to explore potential explanatory factors of players’ perceptions. In total, responses from 1129 players from 44 different countries were analysed. The majority of players expressed a strong preference for the use of Natural Turf pitches over alternatives such as Artificial Turf. The regression model, with a players’ country as a random effect, indicated that players were less favourable towards either Natural Turf or Artificial Turf where there was perceived to be greater variability in surface qualities or the surface was perceived to have less desirable properties. Player’s surface experience was also linked to their overall attitudes, with a suggestion that the quality of the Natural Turf surface players experienced dictated players’ support for Artificial Turf.     

Criterion for the Selection of a Working Correlation Structure in the Generalized Estimating Equation Approach for Longitudinal Balanced Data

The generalized estimating equation is a popular method for analyzing correlated response data. It is important to determine a proper working correlation matrix at the time of applying the generalized estimating equation since an improper selection sometimes results in inefficient parameter estimates. We propose a criterion for the selection of an appropriate working correlation structure. The proposed criterion is based on a statistic to test the hypothesis that the covariance matrix equals a given matrix, and also measures the discrepancy between the covariance matrix estimator and the specified working covariance matrix. We evaluated the performance of the proposed criterion through simulation studies assuming that for each subject, the number of observations remains the same. The results revealed that when the proposed criterion was adopted, the proportion of selecting a true correlation structure was generally higher than that when other competing approaches were adopted. The proposed criterion was applied to longitudinal wheeze data, and it was suggested that the resultant correlation structure was the most accurate.     

Finite mixture of regression models for a stratified sample

Despite the popularity and importance, there is limited work on modelling data which come from complex survey design using finite mixture models. In this work, we explored the use of finite mixture regression models when the samples were drawn using a complex survey design. In particular, we considered modelling data collected based on stratified sampling design. We developed a new design-based inference where we integrated sampling weights in the complete-data log-likelihood function. The expectation–maximisation algorithm was developed accordingly. A simulation study was conducted to compare the new methodology with the usual finite mixture of a regression model. The comparison was done using bias-variance components of mean square error. Additionally, a simulation study was conducted to assess the ability of the Bayesian information criterion to select the optimal number of components under the proposed modelling approach. The methodology was implemented on real data with good results.     

Cousins: Charles Darwin, Sir Francis Galton and the birth of eugenics

Sir Francis Galton, scientist, African Explorer and statistician, was a key figure in statistical history. He was the man who devised the statistical concepts of regression and correlation. He was also Charles Darwin's cousin. And, inspired by his reading of Darwin, he was the founder of eugenics: the "science" of improving the human race through selective breeding. Nicholas Gillham tells of a darker side to statistics and heredity.     

Estimating the Relative Density of Snapper in and around a Marine Reserve Using a Log-Linear Mixed-Effects Model

Angling from small recreational fishing boats was used as a sampling method to quantify the relative density of snapper ( Pagrus auratus ) in six areas within the Cape Rodney-Okakari Point Marine Reserve (New Zealand) and four areas adjacent to the reserve. Penalized quasi-likelihood was used to fit a log-linear mixed-effects model having area and date as fixed effects and boat as a random effect. Simulation and first-order bias correction formulae were employed to assess the validity of the estimates of the area effects. The bias correction is known to be unsuitable for general use because it typically over-estimatesbias, and this was observed here. However, it was qualitatively useful for indicating the direction of bias and for indicating when estimators were approximately unbiased. The parameter of primary interest was the ratio of snapper density in the marine reserve versus snapper density outside the reserve, and the estimator of this parameter was first-order asymptotically unbiased. This ratio of snapper densities was estimated to be 11 (±3).