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arXiv 2025年

作者： Chen, Yuting Lahiri, Partha Salvati, Nicola Joint Program in Survey Methodology University of Maryland College Park United States Department of Economics and Management University of Pisa Italy

This paper extends the Nested Error Regression Model with High-Dimensional Parameters (NERHDP) to address challenges in small area poverty estimation. Building on the NERHDP framework, we develop a robust and flexible approach to derive empirical best predictors (EBPs) of small area poverty indicators, while accommodating heterogeneity in regression coefficients and sampling variances across areas. To overcome computational limitations in the existing algorithm, we introduce an efficient method that significantly reduces computation time, enhancing scalability for large datasets. Additionally, we propose a novel method for generating area-specific poverty estimates for out-of-sample areas, improving the reliability of synthetic estimates. To quantify uncertainty, we introduce a parametric bootstrap method tailored to the extended model. Through design-based simulation studies, we demonstrate that the proposed method has better performance in terms of relative bias and relative root mean squared prediction error compared to existing approaches. Furthermore, the proposed method is applied to household survey data from the 2002 Albania Living Standards Measurement survey to estimate poverty indicators for 374 municipalities using auxiliary information from the 2001 census. © 2025, CC BY-NC-SA.

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An Introduction to Bayesian Inference for Finite Population Characteristics 1

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International Conference on Importance of Statistics in Global Emerging, ISGES 2020

作者： Sedransk, J. Joint Program in Survey Methodology University of Maryland College ParkMD United States

ISBN: (数字)9789811679322

ISBN: (纸本)9789811679315

With an increased interest in using Bayesian methods for the analysis of sample survey data, it is timely to provide an introduction. We start from first principles, progressing to relatively simple parametric models. With the latter one can see how the likelihood and prior information are combined to make inferences. Assuming that the values of Y in the finite population come from a normal distribution with known variance, a sample of size n, and a conjugate prior distribution, explicit expressions for the posterior mean and variance of the finite population mean and variance are presented and interpreted. In a similar way, explicit expressions are given for the case where the finite population is generated from a linear regression of Y on X through the origin. This is a model typically seen in establishment surveys where Yi and Xi represent the survey and census values for unit i. A useful extension when there is hidden cluster structure in the data is to use a Dirichlet process rather than simple parametric models such as those described in this chapter. Multiple regression with post-stratification (MRP) is based on the use of many categorical variables and specialized hierarchical priors. MRP has seen widespread application, especially when the data are from nonprobability samples or probability samples with low response rates. Finally, there is an extensive discussion of alternative (Bayesian) inferential methods when the data are categorical. This is an attractive option when one wishes to avoid postulating parametric continuous distributions. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： surveys

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Microdata access and labor market research: The U.S. experience

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Allgemeines Statistisches Archiv 2005年第2期89卷 121-139页

作者： Abraham, Katharine G. University of Maryland Joint Program in Survey Methodology 1218 LeFrak Hall College Park MD 20742 United States

The paper illustrates the value of broad researcher access to survey and administrative microdata using examples drawn from the U. S. experience, outlining how analyses of trends in earnings inequality, poverty and employment dynamics using such data have benefited policy makers and contributed to improvements in statistical agency data products. Methods of facilitating researcher access, including the release of public use files, the use of licensing agreements, and the establishment of research data centers, are discussed. © Physica-Verlag 2005.

关键词： Labor market research Licensing agreement Microdata access Public use file Research data center

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Increasing fieldwork efficiency through prespecified appointments

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Journal of survey Statistics and methodology 2014年第2期2卷 210-223页

作者： Kreuter, Frauke Mercer, Andrew Hicks, Wendy Survey Methodology University of Maryland College Park United States Institute for Employment Research/LMU Germany Joint Program in Survey Methodology University of Maryland College Park Westat Rockville MD United States Westat Rockville MD United States

Responsive survey designs may attempt to tailor contact attempts to selected units based on available information about the units. Cross-sectional surveys often lack sufficient information for such tailoring, especially at the beginning of the field period. In panel surveys, on the other hand, information from prior waves exists, and such information can be used to refine attempts to make contact or elicit cooperation. However, existing findings regarding the effectiveness of such information are confounded with interviewers' and respondents' behaviors. This research note reports results from a randomized field experiment that tested the use of prior wave contact information to increase field-work efficiency in a face-to-face survey. A random subset of respondents to the Medical Expenditure Panel survey Household Component was informed via postcard about a prespecified interview appointment. The date and time of the appointment were based on information from the prior wave interview date. Such date assignment significantly reduced the number of actions needed to achieve an interview in the treatment group compared to the control group, reducing the number of hours worked in the field by 4 percent.

关键词： surveyS FIELD work (Research) SUBSET selection CROSS-sectional method RESEARCH methodology PUBLIC opinion polls

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Public Opinion Quarterly 2017年第S1期81卷 245-246页

作者： Jans, Matt University of California Los Angeles California Health Interview Survey Joint Program in Survey Methodology

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Estimation of mode effects in the health and retirement study using measurement models

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Journal of survey Statistics and methodology 2016年第4期4卷 501-524页

作者： Cernat, Alexandru Couper, Mick P. Ofstedal, Mary Beth The University of Manchester United Kingdom The Survey Research Center Institute for Social Research University of Michigan United States Survey Research Center and the Population Studies Center Institute for Social Research University of Michigan United States The Joint Program in Survey Methodology University of Maryland United States

Using multiple modes to collect data is becoming a standard practice in surveys. While this should lower costs and reduce nonresponse error, it may have detrimental effects on measurement quality. This is of special concern in panel surveys where a key focus is on measuring change over time and where changing modes may have an effect on key measures. In this paper, we use a quasi-experimental design from the Health and Retirement Study to compare the measurement quality of two scales between face-to-face, telephone, and Web modes. Panel members were randomly assigned to receive a telephone survey or enhanced face-to-face survey in the 2010 core wave, while this was reversed in the 2012 core wave. In 2011, panelists with Internet access completed a Web survey containing selected questions from the core waves. We examine the responses from 3,251 respondents who participated in all three waves, using latent variable models to identify measurement mode effects. The two scales, depression and physical activity, show systematic differences between interviewer-administered modes (i.e., face-to-face and telephone) and the self-administered one (i.e., Web). Possible explanations are discussed.

关键词： Longitudinal study Measurement models Mixed modes Mode effects

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Synthetic time series technique for predicting network-wide road traffic

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Statistical Journal of the IAOS 2018年第3期34卷 425-437页

作者： Cirillo, Cinzia Han, Ying Kaushik, Kartik Lahiri, Parthasarathi Department of Civil and Environmental Engineering University of Maryland MD United States Department of Mathematics University of Maryland MD United States Joint Program in Survey Methodology University of Maryland MD United States

Short term traffic forecasting cannot be more important in the current world of cash strapped economies, placing ever increasing importance on managing existing facilities as opposed to building new infrastructure. The advent of autonomous vehicles further stresses the need for robust and fast frameworks to forecast traffic over the horizon of a typical trip length so that the best routing decision might be made. There is an extensive amount of research on this topic already. However, most of the techniques in literature do not scale well with data or the size of the network in terms of model complexity, computational power and time. Proposed in this paper is a flexible synthetic time series framework that aims to solve the complexity and scalability problems with most models in literature. The synthetic time series framework takes advantage of the repeatability of the traffic patterns such that real-time predictions can be quickly made. It is flexible enough to work with most models in literature, and extendable quite easily with additional parameters to make predictions more robust. Presented in this work are the Autoregressive Integrated Moving Average (ARIMA) models within the synthetic time series framework. It is shown that reasonably accurate predictions can be made by using just the basic structure of ARIMA without any auxiliary variables accounting for the upstream/downstream conditions, incidents or weather. With a robust model fitted within the synthetic framework, prediction errors can be further reduced, while ensuring scalable computation power. Predictions are performed online, where incoming data is fed to the fitted model as the independent variable, and predictions are obtained as the dependent variable. © 2018-IOS Press and the authors. All rights reserved.

关键词： ARIMA network probe data Traffic forecasting

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When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes 2

When Small Decisions Have Big Impact: Fairness Implications ...

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2nd European Workshop on Algorithmic Fairness, EWAF 2023

作者： Kern, Christoph Bach, Ruben L. Mautner, Hannah Kreuter, Frauke Department of Statistics LMU Munich Germany Mannheim Centre for European Social Research University of Mannheim Germany dmTECH Karlsruhe Germany Joint Program in Survey Methodology University of Maryland United States

Algorithmic profiling is increasingly used in the public sector with the hope to allocate limited public resources more effectively and objectively. One example is the prediction-based profiling of job seekers to guide the allocation of support measures by public employment services. However, empirical evaluations of unintended discrimination and fairness concerns are rare in this context. We systematically compare and evaluate statistical models for predicting job seekers’ risk of becoming long-term unemployed with respect to subgroup prediction performance, fairness metrics, and vulnerabilities to data analysis decisions using large-scale German administrative data. We show that despite achieving high prediction performance on average, profiling models can be considerably less accurate for vulnerable social subgroups and that different classification policies can have very different fairness implications. © 2023 Copyright for this paper by its authors.

关键词： Forecasting

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Gauging the impact of growing nonresponse on estimates from a national RDD telephone survey

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PUBLIC OPINION QUARTERLY 2006年第5期70卷 759-779页

作者： Keeter, Scott Kennedy, Courtney Dimock, Michael Best, Jonathan Craighill, Peyton scott keeter is with the Pew Research Center. courtney kennedy is with the Pew Research Center and the Joint Program in Survey Methodology. michael dimock is with the Pew Research Center. jonathan best is with Princeton Survey Research Associates International. peyton craighill is with ABC News.

Declining contact and cooperation rates in random digit dial (RDD) national telephone surveys raise serious concerns about the validity of estimates drawn from such research. While research in the 1990s indicated that nonresponse bias was relatively small, response rates have continued to fall since then. The current study replicates a 1997 methodological experiment that compared results from a "Standard" 5-day survey employing the Pew Research Center's usual methodology with results from a "Rigorous" survey conducted over a much longer field period and achieving a significantly higher response rate. As with the 1997 study, there is little to suggest that unit nonresponse within the range of response rates obtained seriously threatens the quality of survey estimates. In 77 out of 84 comparable items, the two surveys yielded results that were statistically indistinguishable. While the "Rigorous" study respondents tended to be somewhat less politically engaged, they did not report consistently different behaviors or attitudes on other kinds of questions. With respect to sample composition, the Standard survey was closely aligned with estimates from the U.S. Census and other large government surveys on most variables. We extend our analysis of nonresponse to include comparisons with the hardest-to-reach respondents and with respondents who terminated the interview prior to completion.

关键词： TELEPHONE surveys -- Response rate TELEPHONE surveys -- Random digit dialing surveyS -- Research SAMPLING (Statistics) NONRESPONSE (Statistics) STATISTICS QUANTITATIVE research RESPONDENTS

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Handling missing data in survey research

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Statistical Methods in Medical Research 1996年第3期5卷 215-238页

作者： Brick, J.M. Kalton, G. Westat Inc. Rockville MD United States Joint Program in Survey Methodology University of Maryland College Park MD United States Westat Inc. Rockville MD 20850-3129 1650 Research Boulevard United States

Missing data occur in survey research because an element in the target population is not included on the survey's sampling frame (noncoverage), because a sampled element does not participate in the survey (total nonresponse) and because a responding sampled element fails to provide acceptable responses to one or more of the survey items (item nonresponse). A variety of methods have been developed to attempt to compensate for missing survey data in a general purpose way that enables the survey's data file to be analysed without regard for the missing data. Weighting adjustments are often used to compensate for noncoverage and total nonresponse. Imputation methods that assign values for missing responses are used to compensate for item nonresponses. This paper describes the various weighting and imputation methods that have been developed, and discusses their benefits and limitations.

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