Respondent-driven sampling as Markov chain Monte Carlo

Statistics in Medicine

Volumn 28, Issue 17, 2009, Pages 2202-2229

  Goel, Sharad ^a   Salganik, Matthew J ^b  

^a YAHOO RESEARCH   (United States)

^b PRINCETON UNIVERSITY   (United States)

Author keywords

Hard to reach populations; Hidden populations; HIV surveillance; Importance sampling; Markov chain Monte Carlo; Respondent driven sampling; Social networks; Spectral gap

Indexed keywords

ALGORITHM; ARTICLE; CONTROLLED STUDY; DISEASE SURVEILLANCE; HIDDEN MARKOV MODEL; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; INFORMATION PROCESSING; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MEDICAL RESEARCH; MONTE CARLO METHOD; PROBABILITY; RANDOM SAMPLE; SAMPLING; SOCIAL NETWORK;

ALGORITHMS; BIOMETRY; EPIDEMIOLOGIC METHODS; FEMALE; HIV INFECTIONS; HUMANS; MALE; MARKOV CHAINS; MODELS, STATISTICAL; MONTE CARLO METHOD; NEW YORK CITY; PUBLIC HEALTH; SAMPLING STUDIES; SOCIAL SUPPORT; SUBSTANCE-RELATED DISORDERS;

EID: 69949089097     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3613     Document Type: Article

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