书面调查和网络调查的区别——两种数据收集方法的比较

随着网络调查的兴起,研究者必须确认网络调查与传统的纸笔调查效果是否相同。从数据收集质量和测量效果两个方面对纸笔调查与网络调查进行了比较。研究发现：纸笔调查与网络调查的测量模型和测量信度没有显著差异,但是,纸笔调查的测量均值高于网络调查,而网络调查的测量误差高于纸笔调查,网络调查的缺失率更低,纸笔调查与网络调查具有测量不变性。     

DELIBERATELY BIASING SURVEY QUESTIONS

In “before” and “after” surveys of Attitudes Towards Random Breath Testing in South Australia, three basic versions of the questionnaire were used. In the first, a set of “lead-up” questions, which were designed to deliberately bias the results towards acceptance of the tests, was included before the main questions; in the second, there were no lead-up questions; in the third, a different set of lead-up questions was used, and was aimed at deliberately biasing the results against the tests. The results in two out of the four attempts to influence the answers (compared with no lead-up questions) were significant in the expected direction, and in the other two cases were in the correct direction but not significant. The difference between the positive-and negative-biasing versions was highly significant in both cases. It is important to be aware that changes in context rather than in question wording per se can give rise to effects which dwarf the sampling error.     

On the planning and design of sample surveys

Surveys rely on structured questions used to map out reality, using sample observations from a population frame, into data that can be statistically analyzed. This paper focuses on the planning and design of surveys, making a distinction between individual surveys, household surveys and establishment surveys. Knowledge from cognitive science is used to provide guidelines on questionnaire design. Non-standard, but simple, statistical methods are described for analyzing survey results. The paper is based on experience gained by conducting over 150 customer satisfaction surveys in Europe, America and the Far East.     

Teaching Survey Sampling Using Simulation

SURVEY is a computer program that simulates samples drawn from a hypothetical county. We use SURVEY in introductory and advanced sample survey classes to allow students to become involved in all stages of the sampling process, from designing the survey, to analyzing it, to dealing with nonresponse.     

Sampling within households in household surveys

Summary.  The number of people to select within selected households has significant consequences for the conduct and output of household surveys. The operational and data quality implications of this choice are carefully considered in many surveys, but the effect on statistical efficiency is not well understood. The usual approach is to select all people in each selected household, where operational and data quality concerns make this feasible. If not, one person is usually selected from each selected household. We find that this strategy is not always justified, and we develop intermediate designs between these two extremes. Current practices were developed when household survey field procedures needed to be simple and robust; however, more complex designs are now feasible owing to the increasing use of computer-assisted interviewing. We develop more flexible designs by optimizing survey cost, based on a simple cost model, subject to a required variance for an estimator of population total. The innovation lies in the fact that household sample sizes are small integers, which creates challenges in both design and estimation. The new methods are evaluated empirically by using census and health survey data, showing considerable improvement over existing methods in some cases.     

On Sample Allocation in Multivariate Surveys

The problem of a sample allocation between strata in the case of multiparameter surveys is considered in this article. There are several multivariate sample allocation methods and, moreover, several criteria to deal with in such a case. A maximum coefficient of variation of estimators of the population mean of characters under study is taken as the optimality criterion. This article contains a study on a group of the methods that are easy to implement and do not need complex numerical computation; however, they all are approximate. Five such methods are presented and compared using a simulation study. Finally, it is shown which methods should be considered when designing a survey in which the multivariate sample allocation is to be involved.     

The problem of outlier tests in sample surveys

Outliers can occur as readily in samples from the finite populations (e.g. in sample surveys) as in samples from infinite populations. However, in the vast literature on outliers there is almost no mention of outlier tests for data from sample surveys. We examine the behaviour of some standard outlier test statistics for infinite populations when these are applied to finite populations, examining their properties by extensive simulation studies. Some anomalous results are obtained Nsuggesting a fundamental difficulty in testing outliers for the finite population case.     

Target detection from a classical and a Bayesian viewpoint

Two approaches have been used for designing spatial surveys to detect a target. The classical approach controls the probability of missing a target that exists; a Bayesian approach controls the probability that a target exists given that none was seen. In both cases, information about the likely size of the target can reduce sampling requirements. In this paper, previous results are summarized and then used to assess the risk that Roman remains could be present at sites scheduled for development in Greater London.     

The Australian Census Longitudinal Dataset: using record linkage to create a longitudinal sample from a series of cross‐sections

The Australian Bureau of Statistics is creating a longitudinal sample, called the Australian Census Longitudinal Dataset (ACLD), by linking person records across its five‐yearly Census of Population and Housing. This paper proposes a Multi‐Panel framework for selecting and weighting records in the ACLD. This framework can be applied more generally to selecting longitudinal samples from a series of cross‐sectional administrative files. The proposed framework avoids some significant limitations of the popular ‘Top‐Up’ sampling approach to maintaining the cross‐sectional and longitudinal representativeness of a sample over time.     

网络调查中的非抽样误差及其预防措施

互联网的迅速发展,给统计调查方法带来了巨大的影响,在互联网的基础之上发展起来的网络调查方法,以其独特的优势,日益受到人们的青睐。本文结合调查误差分析的理论,根据网络自身的特点,分析了网络调查的非抽样误差的来源,并提出了减少误差的方法。     

住户调查中代表性样本的一种探索获取方法——平衡抽样设计

住户调查是我国社会经济统计调查体系的重要组成部分,样本代表性直接决定统计数据质量。多阶段抽样中初级单元的方差对估计的影响是主要的,因此本文结合2010年全国第六次人口普查分县数据,采用平衡抽样设计获取初级单元的代表性样本-平衡样本。对代表性样本的事后评估结果表明,样本结构与总体结构吻合,目标估计的误差很小,说明了本文平衡设计的有效性。     

A Simple Demonstration of the Relationship between Classification and Canonical Variates Analysis

The purpose of this article is to provide a perspective on present technology for acquisition of information relative to the status of renewable natural resources, with particular emphasis on forest and marine resources. Commonalities and dichotomies are emphasized in the hope of achieving a synthesis that will promote shared understanding and dialogue between statisticians and natural resource discipline specialists, with the ultimate goal being improved survey methodology.     

General class of estimators in multi-character surveys

In this paper, a general class of estimators for the estimation of a finite population total in multi-character surveys is proposed. It is shown that the estimators proposed by Arnab (2002), Amahiaet al. (1989) and Bansal and Singh (1985) are the special cases of the proposed class of estimators. The proposed class of estimators is always more efficient than the estimator proposed by Rao (1966).     

Estimation of Population Means in Multivariate Stratified Random Sampling

In multivariate surveys where p (> 1) characteristics are defined on each unit of the population, the problem of allocation becomes complicated. In the present article, we propose a method to work out the compromise allocation in a multivariate stratified surveys. The problem is formulated as a Multiobjective Integer Nonlinear Programming Problem. Using the value function technique, the problem is converted into a single objective problem. A formula for continuous sample sizes is obtained using Lagrange Multipliers Technique (LMT) that can provide a near optimum solution in some cases. It may give an initial point for any integer nonlinear programing technique.     

A Two-Stage Sequential Sampling Scheme for Warner's Randomized Response Model

Abstract

In this article we revisit Warner's (Warner, S. L. (1965 Warner, S. L. 1965. Randomized Response: a survey technique for elimination evasive answer bias. Journal of the American Statistical Association, 60: 63–69. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). Randomized response: a survey technique for elimination evasive answer bias. Journal of the American Statistical Association 60:63–69) randomize response model for estimating the proportion of “sensitive” attributed in a population and propose a two-stage sequential sampling procedure for it. We show that the new procedure can potentially reduce, on the average, the number of interviewees surveyed in the study while allowing instances with smaller error of estimation. The properties and some of the attractive features of the randomized response two-stage sequential sampling estimation procedure is discussed as illustrated.     

Combining information from multiple surveys for assessing health disparities

Despite advances in public health practice and medical technology, the disparities in health among the various racial/ethnic and socioeconomic groups remain a concern which has prompted the Department of Human and Health Services to designate the elimination of disparities in health as an overarching goal of Healthy People 2010. To assess the progress towards this goal, suitable measures are needed at the population level that can be tracked over time; Statistical inferential procedures have to be developed for these population level measures; and the data sources have to be identified to allow for such inferences to be conducted. Popular data sources for health disparities research are large surveys such the National Health and Interview Survey (NHIS) or the Behavior Risk Factor Surveillance System (BRFSS). The self-report disease status collected in these surveys may be inaccurate and the errors may be correlated with variables used in defining the groups. This article uses the National Health and Nutritional Examination Survey (NHANES) 99-00 to assess the extent of error in the self-report disease status; uses a Bayesian framework develop corrections for the self-report disease status in the National Health Interview Survey (NHIS) 99-00; and compares inferences about various measures of health disparities, with and without correcting for measurement error. The methodology is illustrated using the disease outcome hypertension, a common risk factor for cardiovascular disease. JEL classification C1 (C11, C13, C15), C4 (C42) and I3 (I31, I38)     

Bootstrapping mean‐squared errors of robust small‐area estimators: Application to the method‐of‐payments surveys data

This paper proposes a new bootstrap procedure for mean‐squared errors of robust small‐area estimators. We formally prove the asymptotic validity of the proposed bootstrap method and examine its finite‐sample performance through Monte Carlo simulations. The results show that our procedure performs well and competes with existing ones. We also provide an application to the estimation of the total volume and value of cash, debit card, and credit card transactions in Canada as well as in its provinces and subgroups of households. In particular, we found that there is a significant average annual decline rate of 3.1% in the volume of cash transactions and that this decline is relatively higher among high‐income households living in heavily populated provinces. Our bootstrap estimator also provides indicators of quality useful in selecting the best small‐area predictor among several alternatives in practice.     

Dealing with non-ignorable non-response by using an 'enthusiasm-to-respond' variable

In the National Survey of Sexual Attitudes and Lifestyles (NATSSAL), it is recognized that non-response is unlikely to be ignorable. In some surveys, in addition to the response variables of interest, there may also be an 'enthusiasm-to-respond' variable which is expected to be related to the probabilities of item and unit response. Inference techniques to deal with non-ignorable non-response, based on a propensity-to-respond score, can be developed when there are both item and unit non-responders. For the NATSSAL data, an interviewer-measured interviewee embarrassment variable is combined with demographics to produce a score for the propensity to respond. The necessary likelihood development is outlined and alternative approaches to interval estimation are compared. The methodology is illustrated through an estimation of virginity from NATSSAL data.     

Bayesian methods for mark-resighting surveys

We consider the problem of estimating the size of a closed population based on the results of a certain type of mark-resighting sampling design. The design is similar to the commonly used multiple capture-recapture design, yet in some cases economically more feasible and easy to use. Sampling is done by first tagging a number of randomly selected animals with visible markers and later randomly sighting them (for instance, for large animals by visually sampling from a helicopter) and counting the number of tagged animals. In this paper, we look at Bayesian methods for point and interval estimation of population size for this design. An example involving estimation of mountain sheep, a couple of simulated examples and simulation studies are given to demonstrate the advantages of the proposed procedure over the other available approximate procedures.     

Fitting disposition codes to mobile phone surveys: experiences from studies in Finland, Slovenia and the USA

Summary.  Using mobile phones to conduct survey interviews has gathered momentum recently. However, using mobile telephones in surveys poses many new challenges. One important challenge involves properly classifying final case dispositions to understand response rates and non-response error and to implement responsive survey designs. Both purposes demand accurate assessments of the outcomes of individual call attempts. By looking at actual practices across three countries, we suggest how the disposition codes of the American Association for Public Opinion Research, which have been developed for telephone surveys, can be modified to fit mobile phones. Adding an international dimension to these standard definitions will improve survey methods by making systematic comparisons across different contexts possible.