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A Novel Calibration Estimator in Social Surveys

Bibliographic Data

ID2330705
AuthorsAntonio Arcos (0000-0001-6948-7070, University of Granada, Granada, Spain, corresponding author), José Miguel Contreras García (0000-0001-6821-0563, Universidad de Granada), José M Contreras (University of Granada, Granada, Spain), María M Rueda (0000-0003-4733-289X, University of Granada, Granada, Spain), M Rueda (0000-0002-2903-8745, Universidad de Granada)
Year2014
Volume43
Issue3
Pages465-489
Publication date2014-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSociological Methods & Research (JOURNAL)
Journal identifiersISSN: 0049-1241 • E-ISSN: 1552-8294
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/0049124113507906
OpenAlexW1995640663
LanguageEN
References cited26

Social surveys generally assume that a sample of units (students, individuals, employees,...) is observed by two-stage selection from a finite population, which is grouped into clusters (schools, household, companies,...). This design involves sampling from two different populations: the population of schools or primary stage units and the population of students or second-stage units. Calibration estimators for student statistics can be defined by using combined information based on school totals and student totals. Auxiliary information from the units at the two stages can be calibrated by integrated weighting, as proposed by Lemaître and Dufour or Estevao and Särndal. Two calibration estimators for the population total based on unit weights are defined. The first estimator satisfies a calibration equation at the unit level, and the second one, at the cluster level. The proposed estimator shrinks the unit estimator toward the cluster. A simulation study based on two real populations is carried out to study the empirical performance of this shrinkage estimator. The populations studied were obtained from the Programme for International Student Assessment database and from the Spanish Household Budget Survey

A-weighting · Calibration · Cluster (spacecraft) · Cluster sampling · Econometrics · Estimator · Mathematics education · Physics · Population · Sample (material) · Sampling (signal processing) · Sampling design · Sociology · Statistics · Survey sampling · Unit (ring theory) · Weighting · Computer Science · Demography · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference · Survey Sampling and Estimation Techniques

  • Generalized Raking Procedures in Survey Sampling

    Jean-Claude Deville, CARL-ERIK SÄRNDAL et al.•Journal of the American…•1993

  • Calibration Estimators in Survey Sampling

    Jean-Claude Deville, Jean‐claude Deville et al.•Journal of the American…•1992

  • Weighting for Unequal Selection Probabilities in Multilevel Models

    Open Access•DANNY PFEFFERMANN, C J Skinner et al.•Journal of the Royal Statistical…•1998

  • The Role of Sampling Weights When Modeling Survey Data

    DANNY PFEFFERMANN•International Statistical Review•1993

Citation velocityhistorical
Highly citedNo
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