手机调查的技术初探

 随着手机的普及，手机调查将会继网络调查之后的又一种新的调查方法，并具有一定的现实意义。本文主要探讨了手机调查的概念和分类，着重介绍了手机调查的优势，并提出了手机调查的应用设想，同时也阐述了手机调查所存在的主要问题以及对策，最后提出了发展手机调查的若干建议。     

Communication of risk: health hazards from mobile phones

Summary. Possible health hazards from mobile phones arise from the use of the phones themselves and via the base stations that relay signals. Except for an increase in traffic accidents induced by the use of mobile phones in cars the evidence for a health hazard is at most indirect, but it cannot be entirely dismissed; the phones have not been widely used for sufficiently long for direct epidemiological studies to have high sensitivity for detecting any induced incidence of cancer, for example. The background and evidence are briefly reviewed and the steps taken in the UK to make information widely available described.     

Estimation bias of different design and analytical strategies in dual-frame telephone surveys: an empirical evaluation

Dual-frame survey designs have become increasingly popular in large-scale telephone surveys. This is due to the lack of coverage of the traditional landline survey design and the escalating use of cell phones in recent years. Several estimation strategies have been proposed and their properties have been discussed under ideal scenarios, including pseudo-maximum-likelihood estimation, single-frame estimation, and simple composite estimation [C.J. Skinner and J.N.K. Rao, Estimation in dual frame surveys with complex designs, J. Am. Statist. Assoc. 91 (1996), pp. 349–356; S.L. Lohr and J.N.K. Rao, Inference from dual frame surveys, J. Am. Statist. Assoc. 95 (2000), pp. 271–280]. In practice, estimation in dual-frame telephone surveys is vulnerable to biases and errors (e.g. inaccessibility, topic/mode salience, and measurement error). The investigation of the performance of popular dual-frame estimation methods is scarce in real and less ideal scenarios. Through an innovatively designed simulation study, we compare the estimation bias under different sampling designs with various estimation strategies. To reduce bias, different raking strategies are compared. Simulated scenarios incorporating sampling costs are examined for practical considerations. Overall, the cell phone-only design yields results with the least bias and variance. When accurate covariate information is available for post-stratification, raking estimates from the cell phone-any design also perform very well. We also provide SAS macros for this simulation evaluation upon request. Survey practitioners can fine-tune the parameters based on their prior knowledge of the target population and run the simulation under different scenarios to gain more insights into how to optimally design and analyse telephone surveys.     

我国住户调查一体化设计研究

住户调查一体化设计包括对各项住户调查的通盘考虑和与普查、行政记录的有机衔接。首先,在借鉴国际经验和考虑我国实际的基础上,提出我国住户调查一体化设计的两个基本要求;其次,构造出我国住户调查一体化设计的基础框架;最后,充分利用现行国家调查制度的渠道和机制,对住户调查项目按其调查内容特征和内在逻辑关系进行精简、整合,形成以劳动力调查和住户收支与生活状况调查为核心的住户调查体系,并给出以主样本为主体的我国住户调查的一体化设计思路。     

A Note on an Approximation of the Mobile Communications Expenditures Distribution Function Using a Mixture Model

Approximating the distribution of mobile communications expenditures (MCE) is complicated by zero observations in the sample. To deal with the zero observations by allowing a point mass at zero, a mixture model of MCE distributions is proposed and applied. The MCE distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The model is empirically verified for individual MCE survey data collected in Seoul, Korea. The mixture model can easily capture the common bimodality feature of the MCE distribution. In addition, when covariates were added to the model, it was found that the probability that an individual has non-expenditure significantly varies with some variables. Finally, the goodness-of-fit test suggests that the data are well represented by the mixture model.     

关于人口统计调查方法体系存在的问题和改革设想

我国现行的人口统计调查方法体系是“以经常性的人口抽样调查为主体,以人口普查为基础,重点调查等为补充的多种方法的运用”,但随着经济社会的快速发展,“以普查为基础,经常性抽样调查为主体"的人口统计调查方法体系,与政府、社会对人口信息多层次、精细化、时效性的需求变得不适应,在实践中显露出矛盾和问题。本文以下将对当前人口普查和人口变动情况抽样调查,在人口统计中作用和存在问题做出分析,在此基础上提出人口统计的改革设想,并落实到具体的解决办法,以2020年第七次人口普查为契机,建立《人口统计与管理服务数据平台》,并结合社区网格化管理进行年度更新,取得年度全国、省级及省级以下的常住人口数据;同时改革人口抽样调查的内容,结合手机信令大数据在人口统计中的应用,完善人口统计调查方法体系。     

Small domain estimation by empirical bayes and kalman filtering procedures - a case study

An application of empirical Bayes and Kalman filtering tecniques is reported, using live data from Indian Statistical Institute (ISI), Calcutta . to illustrate how initial small domain estimators may be vastly improved upon. A stratified two stage sampling procedure is adopted, allowing selection of first stage units with unequal probabilities but of second stage units with equal probabilities. Standard design-based estimators for domain totals are initialized based on domain specific survey data alone. Strength is then borrowed across domains and from past surveys. The resulting gains in efficacy are numlerically demonstrated, through replicated sampling from official records.     

Statistical data integration using multilevel models to predict employee compensation

This article considers the case where two surveys collect data on a common variable, with one survey being much smaller than the other. The smaller survey collects data on an additional variable of interest, related to the common variable collected in the two surveys, and out-of-scope with respect to the larger survey. Estimation of the two related variables is of interest at domains defined at a granular level. We propose a multilevel model for integrating data from the two surveys, by reconciling survey estimates available for the common variable, accounting for the relationship between the two variables, and expanding estimation for the other variable, for all the domains of interest. The model is specified as a hierarchical Bayes model for domain-level survey data, and posterior distributions are constructed for the two variables of interest. A synthetic estimation approach is considered as an alternative to the hierarchical modelling approach. The methodology is applied to wage and benefits estimation using data from the National Compensation Survey and the Occupational Employment Statistics Survey, available from the Bureau of Labor Statistics, Department of Labor, United States.     

Responsive design for household surveys: tools for actively controlling survey errors and costs

Summary.  Over the past few years surveys have expanded to new populations, have incorporated measurement of new and more complex substantive issues and have adopted new data collection tools. At the same time there has been a growing reluctance among many household populations to participate in surveys. These factors have combined to present survey designers and survey researchers with increased uncertainty about the performance of any given survey design at any particular point in time. This uncertainty has, in turn, challenged the survey practitioner's ability to control the cost of data collection and quality of resulting statistics. The development of computer-assisted methods for data collection has provided survey researchers with tools to capture a variety of process data ('paradata') that can be used to inform cost–quality trade-off decisions in realtime. The ability to monitor continually the streams of process data and survey data creates the opportunity to alter the design during the course of data collection to improve survey cost efficiency and to achieve more precise, less biased estimates. We label such surveys as 'responsive designs'. The paper defines responsive design and uses examples to illustrate the responsive use of paradata to guide mid-survey decisions affecting the non-response, measurement and sampling variance properties of resulting statistics.     

An Evaluation of a Large-scale Cati Household Survey Using Random Digit Dialling

Computer-assisted telephone interviewing and random digit dialling are increasingly being used to conduct household surveys in Australia. However, there is little published information concerning Australian experience with such surveys. In 1995 the Government Statistician's Office in Queensland conducted a household survey to study population migration using these techniques. The survey involved a sample of 110 000 telephone numbers resulting in 38 000 responding households. This article describes a computerized survey management system that was developed and which provided information concerning important operational and quality aspects of the survey.     

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.     

Combining information from multiple surveys by using regression for efficient small domain estimation

Summary.  In sample surveys of finite populations, subpopulations for which the sample size is too small for estimation of adequate precision are referred to as small domains. Demand for small domain estimates has been growing in recent years among users of survey data. We explore the possibility of enhancing the precision of domain estimators by combining comparable information collected in multiple surveys of the same population. For this, we propose a regression method of estimation that is essentially an extended calibration procedure whereby comparable domain estimates from the various surveys are calibrated to each other. We show through analytic results and an empirical study that this method may greatly improve the precision of domain estimators for the variables that are common to these surveys, as these estimators make effective use of increased sample size for the common survey items. The design-based direct estimators proposed involve only domain-specific data on the variables of interest. This is in contrast with small domain (mostly small area) indirect estimators, based on a single survey, which incorporate through modelling data that are external to the targeted small domains. The approach proposed is also highly effective in handling the closely related problem of estimation for rare population characteristics.     

The sensitivity of estimates of the change in population behaviour to realistic changes in bias in repeated surveys

Summary.  The first British National Survey of Sexual Attitudes and Lifestyles (NATSAL) was conducted in 1990–1991 and the second in 1999–2001. When surveys are repeated, the changes in population parameters are of interest and are generally estimated from a comparison of the data between surveys. However, since all surveys may be subject to bias, such comparisons may partly reflect a change in bias. Typically limited external data are available to estimate the change in bias directly. However, one approach, which is often possible, is to define in each survey a sample of participants who are eligible for both surveys, and then to compare the reporting of selected events that occurred before the earlier survey time point. A difference in reporting suggests a change in overall survey bias between time points, although other explanations are possible. In NATSAL, changes in bias are likely to be similar for groups of sexual experiences. The grouping of experiences allows the information that is derived from the selected events to be incorporated into inference concerning population changes in other sexual experiences. We use generalized estimating equations, which incorporate weighting for differential probabilities of sampling and non-response in a relatively straightforward manner. The results, combined with estimates of the change in reporting, are used to derive minimum established population changes, based on NATSAL data. For some key population parameters, the change in reporting is seen to be consistent with a change in bias alone. Recommendations are made for the design of future surveys.     

Small area estimation with auxiliary survey data

Large governmental surveys typically provide accurate national statistics. To decrease the mean squared error of estimates for small areas, i.e., domains in which the sample size is small, auxiliary variables from administrative records are often used as covariates in a mixed linear model. It is generally assumed that the auxiliary information is available for every small area. In many cases, though, such information is available for only some of the small areas, either from another survey or from a previous administration of the same survey. The authors propose and study small area estimators that use multivariate models to combine information from several surveys. They discuss computational algorithms, and a simulation study indicates that if quantities in the different surveys are sufficiently correlated, substantial gains in efficiency can be achieved.     

Multilevel modelling of refusal and non-contact in household surveys: evidence from six UK Government surveys

Summary.  We analyse household unit non-response in six major UK Government surveys by using a multilevel multinomial modelling approach. The models are guided by current conceptual frameworks and theories of survey participation. One key feature of the analysis is the investigation of the extent to which effects of household characteristics are survey specific. The analysis is based on the 2001 UK Census Link Study, which is a unique source of data containing an unusually rich set of auxiliary variables. The study contains the response outcome of six surveys, linked to census data and interviewer observations for both respondents and non-respondents.     

Regression Coefficient Estimation in Dual Frame Surveys

Dual frame surveys, in which independent samples are selected from two frames to decrease survey costs or to improve coverage, can present challenges for regression coefficient estimation because of complex designs and unknown degree of overlap. In this research, we developed four regression coefficient estimators in dual frame surveys. Simulation results show that all the proposed methods work well.     

On randomized response surveys for estimating a proportion

In studies about sensitive characteristics, randomized response (RR) methods are useful for generating reliable data, protecting respondents’ privacy. It is shown that all RR surveys for estimating a proportion can be encompassed in a common model and some general results for statistical inferences can be used for any given survey. The concepts of design and scheme are introduced for characterizing RR surveys. Some consequences of comparing RR designs based on statistical measures of efficiency and respondent’ protection are discussed. In particular, such comparisons lead to the designs that may not be suitable in practice. It is suggested that one should consider other criteria and the scheme parameters for planning a RR survey.     

New statistical needs concerning the estimation of the demographic changes taking place in Poland

The authors examine the increased need for survey data in Poland to keep track of the rapid economic, social, and demographic changes that are occurring in the country. They discuss the type of surveys that are needed and such topics as data compatibility, sampling, frequency, and organization of data collection through surveys. (ANNOTATION)     

Surveying migrant households: a comparison of census-based, snowball and intercept point surveys

Summary.  Few representative surveys of households of migrants exist, limiting our ability to study the effects of international migration on sending families. We report the results of an experiment that was designed to compare the performance of three alternative survey methods in collecting data from Japanese–Brazilian families, many of whom send migrants to Japan. The three surveys that were conducted were households selected randomly from a door-to-door listing using the Brazilian census to select census blocks, a snowball survey using Nikkei community groups to select the seeds and an intercept point survey that was collected at Nikkei community gatherings, ethnic grocery stores, sports clubs and other locations where family members of migrants are likely to congregate. We analyse how closely well-designed snowball and intercept point surveys can approach the much more expensive census-based method in terms of giving information on the characteristics of migrants, the level of remittances received and the incidence and determinants of return migration.