This paper is in the following e-collection/theme issue:

Descriptive Epidemiology and Population Size Estimates (85) HIV/AIDS/STI Prevention and Care (816) Statistical Methods for Surveillance and Population Health (146) Validity, Reliability, and Bias (89)

Published on in Vol 6, No 2 (2020): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15044, first published .
Assessing Bias in Population Size Estimates Among Hidden Populations When Using the Service Multiplier Method Combined With Respondent-Driven Sampling Surveys: Survey Study

Assessing Bias in Population Size Estimates Among Hidden Populations When Using the Service Multiplier Method Combined With Respondent-Driven Sampling Surveys: Survey Study

Assessing Bias in Population Size Estimates Among Hidden Populations When Using the Service Multiplier Method Combined With Respondent-Driven Sampling Surveys: Survey Study

Authors of this article:

Sungai T Chabata1 Author Orcid Image ;   Elizabeth Fearon2 Author Orcid Image ;   Emily L Webb3 Author Orcid Image ;   Helen A Weiss3 Author Orcid Image ;   James R Hargreaves4 Author Orcid Image ;   Frances M Cowan1, 5 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Yiasemidou M. The Impact of COVID-19 on Surgical Training: the Past, the Present and the Future. Indian Journal of Surgery 2022;84(S1):131 View
  2. Gutreuter S, Wheldon M. Comparative performance of multiple-list estimators of key population size. PLOS Global Public Health 2022;2(3):e0000155 View