Response Burden, Sample Rotation, and Classification Renewal in Economic Surveys

Sunter, A. B.

doi:10.2307/1402535

Cited by 16 publications

(5 citation statements)

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“…Estimates of prevalence were weighted to account for over-sampling and partially adjusted for non-participation in the social security medical centers [Meffre et al, 2007]. In the first stage, a sampling algorithm [Sunter, 1977b;Sä rndal et al, 2003] was used to calculate the second-order inclusion probabilities to guarantee unbiased and nonnegative Sen-Yates-Grundy's variance estimators of prevalences [Sen, 1953;Yates and Grundy, 1953;Sunter, 1977a]. To represent the French metropolitan population, prevalence estimates were further adjusted by poststratification on age, sex, medical welfare for socially deprived persons and region, using data from the 1999 French census.…”

Section: Discussionmentioning

confidence: 99%

Prevalence of hepatitis B and hepatitis C virus infections in France in 2004: Social factors are important predictors after adjusting for known risk factors

Meffre

Strat

Delarocque-Astagneau

et al. 2010

Journal of Medical Virology

202

161

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To monitor the prevalence of hepatitis B and hepatitis C a cross-sectional survey was conducted in 2004 among French metropolitan residents. A complex sampling design was used to enroll 14,416 adult participants aged 18-80 years. Data collected included demographic and social characteristics and risk factors. Sera were tested for anti-HCV, HCV-RNA, anti-HBc and HBsAg. Data were analyzed with SUDAAN software to provide weighted estimates for the French metropolitan resident population. The overall anti-HCV prevalence was 0.84% (95% CI: 0.65-1.10). Among anti-HCV positive individuals, 57.4% (95% CI: 43.2-70.5) knew their status. Factors associated independently with positive anti-HCV were drug use (intravenous and nasal), blood transfusion before 1992, a history of tattoos, low socioeconomic status, being born in a country where anti-HCV prevalence >2.5%, and age >29 years. The overall anti-HBc prevalence was 7.3% (95%: 6.5-8.2). Independent risk factors for anti-HBc were intravenous drug use, being a man who has sex with men, low socioeconomic status, a stay in a psychiatric facility or facility for the mentally disabled, <12 years of education, being born in a country where HBsAg prevalence >2%, age >29 and male sex. The HCV RNA and HBsAg prevalence were 0.53% (95% CI: 0.40-0.70) and 0.65% (95% CI: 0.45-0.93), respectively. Among HBsAg positive individuals, 44.8% (95% CI: 22.8-69.1) knew their status. Anti-HCV prevalence was close to the 1990s estimates whereas HBsAg prevalence estimate was greater than expected. Screening of hepatitis B and C should be strengthened and should account for social vulnerability.

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Section: Discussionmentioning

confidence: 99%

Prevalence of hepatitis B and hepatitis C virus infections in France in 2004: Social factors are important predictors after adjusting for known risk factors

Meffre

Strat

Delarocque-Astagneau

et al. 2010

Journal of Medical Virology

202

161

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“…The inclusion probabilities have been computed using the auxiliary variable z and the other auxiliary variable x has been used at the estimation stage. From each of the large population, a sample of size n (depending on the population size) was drawn whereas a sample of size n = 6 was drawn from small populations using Sunter's sampling scheme [26,27]. The large populations and small populations are listed in Table A1 of Appendix 1 and Table A2 of Appendix 2, respectively .…”

Section: Simulation Studymentioning

confidence: 99%

A Monte Carlo comparison of some variance estimators of the Horvitz–Thompson estimator

Patel

2010

Journal of Statistical Computation and Simulation

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At the design and estimation stage of a survey, large survey organization often uses auxiliary information. This article discusses various procedures for improving variance estimation of the Horvitz-Thompson estimator of a finite population total with the aid of auxiliary information. To study the design-based properties of the proposed variance estimators relative to the standard one, a small scale Monte Carlo study is performed.

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“…It is interesting to compare V(n'), as given by (11), with the corresponding variance for Poisson sampling (Sunter, 1977b) in which we would sample each unit independently and with probability nzi. In this case the Poisson sample size, n" say, has expected value E(n") = n and variance V(n") = Eri(1 -7ri).…”

Section: Then N' = E T and It Is Easy To Derive E(n ')2=mentioning

confidence: 99%

Solutions to the Problem of Unequal Probability Sampling without Replacement

Sunter¹

1986

International Statistical Review / Revue Internationale de Stat

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JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. International Statistical Institute (ISI) is collaborating with JSTOR to digitize, preserve and extend access to International Statistical Review / Revue Internationale de Statistique. SummaryThe problem of sampling with probability proportional to a measure of size and with certain requirements for the probabilities of joint selection of pairs of units has a history that goes back to about 1943. However, although more than 50 articles on the subject have been published none of them has given a completely satisfactory solution and none of them has emerged, at least for sample sizes greater than two, as a practical alternative to the usual method of systematic sampling with probability proportional to size. The solution given in this paper is exact, simple and intuitively appealing.

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Response Burden, Sample Rotation, and Classification Renewal in Economic Surveys

Cited by 16 publications

References 1 publication

Prevalence of hepatitis B and hepatitis C virus infections in France in 2004: Social factors are important predictors after adjusting for known risk factors

Prevalence of hepatitis B and hepatitis C virus infections in France in 2004: Social factors are important predictors after adjusting for known risk factors

A Monte Carlo comparison of some variance estimators of the Horvitz–Thompson estimator

Solutions to the Problem of Unequal Probability Sampling without Replacement

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