Using interviewer random effects to remove selection bias from HIV prevalence estimates
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Epidemiology
Link
http://link.springer.com/article/10.1186/1471-2288-15-8/fulltext.html
Reference39 articles.
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2. Hogan DR, Salomon JA, Canning D, Hammitt JK, Zaslavsky AM, Bärnighausen T: National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models.Sex Transm Infect 2012,88(Suppl 2):i17–23. 10.1136/sextrans-2012-050636
3. Mishra V, Vaessen M, Boerma J, Arnold F, Way A, Barrere B, et al.: HIV testing in national population-based surveys: experience from the Demographic and Health Surveys.Bull World Health Organ 2006, 84:537–45. 10.2471/BLT.05.029520
4. Marston M, Harriss K, Slaymaker E: Non-response bias in estimates of HIV prevalence due to the mobility of absentees in national population-based surveys: a study of nine national surveys.Sex Transm Infect 2008,84(Suppl 1):i71–7.
5. Mishra V, Barrere B, Hong R, Khan S: Evaluation of bias in HIV seroprevalence estimates from national household surveys.Sex Transm Infect 2008,84(Suppl 1):i63–70.
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