Matthew J. Salganik
Matthew J. Salganik
Department of Sociology, Princeton University
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Sampling and estimation in hidden populations using respondent‐driven sampling
MJ Salganik, DD Heckathorn
Sociological methodology 34 (1), 193-240, 2004
Experimental study of inequality and unpredictability in an artificial cultural market
MJ Salganik, PS Dodds, DJ Watts
Science 311 (5762), 854-856, 2006
Variance estimation, design effects, and sample size calculations for respondent-driven sampling
MJ Salganik
Journal of Urban Health 83 (1), 98, 2006
Assessing respondent-driven sampling
S Goel, MJ Salganik
Proceedings of the National Academy of Sciences 107 (15), 6743-6747, 2010
Leading the herd astray: An experimental study of self-fulfilling prophecies in an artificial cultural market
MJ Salganik, DJ Watts
Social psychology quarterly 71 (4), 338-355, 2008
Respondent‐driven sampling as Markov chain Monte Carlo
S Goel, MJ Salganik
Statistics in medicine 28 (17), 2202-2229, 2009
Bit by bit: social research in the digital age
MJ Salganik
Princeton University Press, 2018
How many people do you know in prison? Using overdispersion in count data to estimate social structure in networks
T Zheng, MJ Salganik, A Gelman
Journal of the American Statistical Association 101 (474), 409-423, 2006
Diagnostics for respondent‐driven sampling
KJ Gile, LG Johnston, MJ Salganik
Journal of the Royal Statistical Society: Series A (Statistics in Society …, 2015
Web‐based experiments for the study of collective social dynamics in cultural markets
MJ Salganik, DJ Watts
Topics in cognitive science 1 (3), 439-468, 2009
How many people do you know?: Efficiently estimating personal network size
TH McCormick, MJ Salganik, T Zheng
Journal of the American Statistical Association 105 (489), 59-70, 2010
Strengthening the reporting of observational studies in epidemiology for respondent-driven sampling studies:“STROBE-RDS” statement
RG White, AJ Hakim, MJ Salganik, MW Spiller, LG Johnston, L Kerr, ...
Journal of clinical epidemiology 68 (12), 1463-1471, 2015
Counting hard-to-count populations: the network scale-up method for public health
HR Bernard, T Hallett, A Iovita, EC Johnsen, R Lyerla, C McCarty, M Mahy, ...
Sexually transmitted infections 86 (Suppl 2), ii11-ii15, 2010
Wiki surveys: Open and quantifiable social data collection
MJ Salganik, KEC Levy
PLoS ONE 10 (5), e0123483, 2015
Assessing network scale-up estimates for groups most at risk of HIV/AIDS: evidence from a multiple-method study of heavy drug users in Curitiba, Brazil
MJ Salganik, D Fazito, N Bertoni, AH Abdo, MB Mello, FI Bastos
American journal of epidemiology 174 (10), 1190-1196, 2011
Commentary: respondent-driven sampling in the real world
MJ Salganik
Epidemiology 23 (1), 148-150, 2012
The game of contacts: estimating the social visibility of groups
MJ Salganik, MB Mello, AH Abdo, N Bertoni, D Fazito, FI Bastos
Social networks 33 (1), 70-78, 2011
Social influence: The puzzling nature of success in cultural markets
MJ Salganik, DJ Watts
The Oxford handbook of analytical sociology, 315-341, 2017
Generalizing the network scale-up method: a new estimator for the size of hidden populations
DM Feehan, MJ Salganik
Sociological Methodology 46 (1), 153-186, 2016
Quantity versus quality: A survey experiment to improve the network scale-up method
DM Feehan, A Umubyeyi, M Mahy, W Hladik, MJ Salganik
American journal of epidemiology 183 (8), 747-757, 2016
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