Estimation Techniques for Ordinal Data in Multiple Frame Surveys with Complex Sampling Designs

Surveys usually include questions where individuals must select one in a series of possible options that can be sorted. On the other hand, multiple frame surveys are becoming a widely used method to decrease bias due to undercoverage of the target population. In this work, we propose statistical techniques for handling ordinal data coming from a multiple frame survey using complex sampling designs and auxiliary information. Our aim is to estimate proportions when the variable of interest has ordinal outcomes. Two estimators are constructed following model‐assisted generalised regression and model calibration techniques. Theoretical properties are investigated for these estimators. Simulation studies with different sampling procedures are considered to evaluate the performance of the proposed estimators in finite size samples. An application to a real survey on opinions towards immigration is also included.     

Household Surveys,Consumption, and the Measurement of Poverty

Household surveys are playing an increasingly important role in the measurement of poverty and well-being around the world. The Living Standards Measurement Study, which was begun in the World Bank under the guidance of Graham Pyatt in 1979, has played an important role in this movement. Its surveys are widely used within the Bank to measure consumption-based poverty, and survey data are now the exclusive basis for the global poverty counts. This paper discusses a number of unresolved issues in using consumption-based surveys for measuring well-being, including the choice of a money-metric versus welfare-ratio approach, the collection of suitable price information, the effects of measurement error on estimation, and methods for correcting per capita consumption for the demographic structure of the household.     

Combining Data from New and Traditional Sources in Population Surveys

This paper is a review of some applications of the combination of data sets, such as combining census or administrative data and survey data, constructing expanded data sets through linkage, combining large‐scale commercial databases with survey data and harnessing designed data collection to be able to make use of non‐probability samples. It is aimed to highlight their commonalities and differences and to formulate some general principles for data set combination.     

Analysis of Categorical Data for Complex Surveys

This paper reviews methods for handling complex sampling schemes when analysing categorical survey data. It is generally assumed that the complex sampling scheme does not affect the specification of the parameters of interest, only the methodology for making inference about these parameters. The organisation of the paper is loosely chronological. Contingency table data are emphasised first before moving on to the analysis of unit‐level data. Weighted least squares methods, introduced in the mid 1970s along with methods for two‐way tables, receive early attention. They are followed by more general methods based on maximum likelihood, particularly pseudo maximum likelihood estimation. Point estimation methods typically involve the use of survey weights in some way. Variance estimation methods are described in broad terms. There is a particular emphasis on methods of testing. The main modelling methods considered are log‐linear models, logit models, generalised linear models and latent variable models. There is no coverage of multilevel models.     

Empirical Likelihood Approach for Aligning Information from Multiple Surveys

When two surveys carried out separately in the same population have common variables, it might be desirable to adjust each survey's weights so that they give equal estimates for the common variables. This problem has been studied extensively and has often been referred to as alignment or numerical consistency. We develop a design-based empirical likelihood approach for alignment and estimation of complex parameters defined by estimating equations. We focus on a general case when a single set of adjusted weights, which can be applied to both common and non-common variables, is produced for each survey. The main contribution of the paper is to show that the impirical log-likelihood ratio statistic is pivotal in the presence of alignment constraints. This pivotal statistic can be used to test hypotheses and derive confidence regions. Hence, the empirical likelihood approach proposed for alignment possesses the self-normalisation property, under a design-based approach. The proposed approach accommodates large sampling fractions, stratification and population level auxiliary information. It is particularly well suited for inference about small domains, when data are skewed. It includes implicit adjustments when the samples considerably differ in size. The confidence regions are constructed without the need for variance estimates, joint-inclusion probabilities, linearisation and re-sampling.     

Reducing Missing Data in Surveys: An Overview of Methods

Although item nonresponse can never be totally prevented, it can be considerably reduced, and thereby provide the researcher with not only more useable data, but also with helpful auxiliary information for a better imputation and adjustment. To achieve this an optimal data collection design is necessary. The optimization of the questionnaire and survey design are the main tools a researcher has to reduce the number of missing data in any such survey. In this contribution a concise typology of missing data patterns and their sources of origin are presented. Based on this typology, the mechanisms responsible for missing data are identified, followed by a discussion on how item nonresponse can be prevented.     

Governance, Democracy and Poverty Reduction: Lessons Drawn from Household Surveys in Sub-Saharan Africa and Latin America

Public statistics face quite a challenge when it comes to measuring new dimensions of development (institutions, governance, and social and political participation). To take up this challenge, modules on Governance, Democracy and Multiple Dimensions of Poverty have been appended to household surveys by National Statistics Institutes in twelve African and Latin American developing countries. This paper presents the issues addressed and the methodological lessons learnt along with a selection of findings to illustrate this innovative approach and demonstrate its analytic potential. We investigate, for instance, the population's support for democratic principles, the respect for civil and political rights and the trust in the political class; the ‘need for the State’, particularly of the poorest; the extent of petty corruption; the reliability of expert surveys on governance; the perception of decentralization policies at local level; the level and vitality of social and political participation, etc. The conclusive appraisal made opens up prospects for the national statistical information systems in the developing countries. The measurement and tracking of this new set of objective and subjective public policy monitoring indicators would benefit from being made systematic.     

On the Use of Auxiliary and Paradata for Dealing With Non‐sampling Errors in Household Surveys

In this paper, we consider the use of auxiliary and paradata for dealing with non‐response and measurement errors in household surveys. Three over‐arching purposes are distinguished: response enhancement, statistical adjustment, and bias exploration. Attention is given to the varying focus at the different phases of statistical production from collection, processing to analysis, and how to select and utilize the useful auxiliary and paradata. Administrative register data provide the richest source of relevant auxiliary information, in addition to data collected in previous surveys and censuses. Due to their importance in effective dealings with non‐sampling errors, one should make every effort to increase their availability in the statistical system and, at the same time, to develop efficient statistical methods that capitalize on the combined data sources.     

Sick-leave and Other Job-related Health Issues from Labour Force Surveys Data

Most research into the relationship between health and work has been limited to ad hoc studies: few studies have been based on large-sample surveys directed to the general population. We propose here approaches to developing work-related health indicators from currently collected National Labour Force Surveys, in particular the Italian Labour Force Survey-ISTAT. Four potential indicators are proposed: temporary reduction in working ability (TRWA), continued reduction in working ability (CRWA), permanent inability to work (PIW), and exclusion from the active population (EAP). Our analysis indicates that CRWA and EAP are highest among manual workers, consistent with the well-described relationship between job class and health status. This approach provides an opportunity to monitor the relative health status of workers on a continuing basis using readily available, population-based data and to conduct additional analyses on the basis of occupational stratification.     

中、日、韩企业质量绩效调查对比分析

文章论述了企业质量绩效评价的意义及进展情况,重点介绍了中、日、韩三国企业质量绩效调查的现状,并从目的、运作方式、调查方式、评价指标、调查结果的使用等几个方面进行了对比分析。     

Combining Data from Surveys and Administrative Record Systems. The Norwegian Experience

At Statistics Norway administrative data have been extensively used in order to improve the quality of survey data. Various techniques have been used to reduce sampling variance and/or to reduce the effects of non-response. In the present article some of the most commonly used methods are being presented, and based on empirical rather than theoretical evaluations, we give our conclusions concerning their potentials and limitations.     

Design‐based Estimators Calibrated on Estimated Totals from Multiple Surveys

The use of auxiliary variables to improve the efficiency of estimators is a well‐known strategy in survey sampling. Typically, the auxiliary variables used are the totals of appropriate measurement that are exactly known from registers or administrative sources. Increasingly, however, these totals are estimated from surveys and are then used to calibrate estimators and improve their efficiency. We consider different types of survey structures and develop design‐based estimators that are calibrated on known as well as estimated totals of auxiliary variables. The optimality properties of these estimators are studied. These estimators can be viewed as extensions of the Montanari generalised regression estimator adapted to the more complex situations. The paper studies interesting special cases to develop insights and guidelines to properly manage the survey‐estimated auxiliary totals.     

The Effect of Follow-up Mailings on The Response Rate and Response Quality in Mail Surveys

Numerous experts have demonstrated that the increase in the number of contacts produces a “lengthening” of the field work, although this lag in the analysis of the data is “compensated” by the increase in the response rate that is achieved through this second, third, and successive “contacts”. However, can it be said that these interviewees respond with the same dedication as those who responded from the initial contact? Or could it be that they will try to respond “hastily” so as not to be “harassed” further? The aim of this study is to try to find some answers to these questions by giving the results of the first ever research carried out in Spain using the TDM of Dillman in mail surveys.     

浅谈家庭用开关、插头插座质量问题

我国很多的火灾事故都是由于开关与插头插座质量不过关引起,导致家庭用开关与插头插座出现质量问题的因素包括两个方面,第一是由于生产开关与插头插座的科技含量不高,第二是用户的因素。本文主要分析家庭用开关、插头插座的常见质量问题。     

质量管理体系中的数据分析

1 获证组织质量管理体系“数据分析”中存在的主要问题。“数据分析”在质量管理体系中具有重要地位,体系运行的有效性如何,与数据分析有着重要的关系.笔者审核了300余家不同行业的质量管理体系,发现“数据分析”这个过程运行好的企业不多,是ISO 9000标准中实施得最差的条款之一.归纳起来,主要存在以下问题：     

数据挖掘在质量管理体系中的应用

数据挖掘技术提供了对海量质量数据的强大分析处理功能。本文分析了质量管理体系中质量数据的特点，提出了质量数据挖掘系统的系统模型和分层体系结构；并介绍了质量数据挖掘的主要模型及方法，包括质量预测模型、分类模型和关联模型。     

海洋地震资料多次波压制技术及应用

近些年来,随着陆上油气资源的日益枯竭,为扩大资源的开采,地震勘探的发展由陆地逐渐向海洋,因此对于海洋地震资料处理技术的研究就变得更有意义和价值。海上地震数据当中最主要的干扰是多次波,因此如何有效压制多次波,是目前海洋地震资料处理的主要课题之一。文章对多次波的成因及分类,多次波的特征及识别、多次波压制方法进行归纳总结。     

Modelling Strategies for Repeated Multiple Response Data

This article discusses modelling strategies for repeated measurements of multiple response variables. Such data arise in the context of categorical variables where one can select more than one of the categories as the response. We consider each of the multiple responses as a binary outcome and use a marginal (or population‐averaged) modelling approach to analyse its means. Generalized estimating equations are used to account for different correlation structures, both over time and between items. We also discuss an alternative approach using a generalized linear mixed model with conditional interpretations. We illustrate the methods using data from a panel study in Australia called the Household, Income, and Labour Dynamics Survey.     

简析分户验收中常见质量问题及处理措施

分户验收工作是检验住宅建筑施工中工程质量的重要环节,随着社会对质量控制及管理的日益重视,分户验收的理念越来越深入人心。文章从分户验收的内容、存在的问题和处理措施3个方面进行论述。