Nonresponse in repeat population-based voluntary counseling and testing for HIV in rural Malawi
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DOI: 10.1353/dem.0.0115
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Cited by:
- Bruno Arpino & Elisabetta De Cao & Franco Peracchi, 2011.
"Using panel data to partially identify HIV prevalence When HIV status is not missing at random,"
Working Papers
048, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
- Bruno Arpino & Elisabetta De Cao & Franco Peracchi, 2011. "Using panel data to partially identify HIV prevalence when HIV status is not missing at random," EIEF Working Papers Series 1113, Einaudi Institute for Economics and Finance (EIEF), revised Aug 2011.
- Wendy Janssens & Jacques Gaag & Tobias Rinke de Wit & Zlata Tanović, 2014. "Refusal Bias in the Estimation of HIV Prevalence," Demography, Springer;Population Association of America (PAA), vol. 51(3), pages 1131-1157, June.
- McGovern, Mark E. & Canning, David & Bärnighausen, Till, 2018. "Accounting for non-response bias using participation incentives and survey design: An application using gift vouchers," Economics Letters, Elsevier, vol. 171(C), pages 239-244.
- Giampiero Marra & Rosalba Radice & Till Bärnighausen & Simon N. Wood & Mark E. McGovern, 2017.
"A Simultaneous Equation Approach to Estimating HIV Prevalence With Nonignorable Missing Responses,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 484-496, April.
- Giampiero Marra & Rosalba Radice & Till Bärnighausen & Simon N. Wood & Mark E. McGovern, 2016. "A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses," Economics Working Papers 16-02, Queen's Management School, Queen's University Belfast.
- Tomoki Fujii & Denis H.Y. Leung, 2014. "Bound estimator of HIV prevalence: Application to Malawi," Working Papers 17-2014, Singapore Management University, School of Economics.
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