A simulative comparison of respondent driven sampling with incentivized snowball sampling - The "strudel effect"

V. Anna Gyarmathy, Lisa G. Johnston, Irma Caplinskiene, Saulius Caplinskas, Carl A. Latkin

    Research output: Contribution to journalArticle

    8 Citations (Scopus)

    Abstract

    Background: Respondent driven sampling (RDS) and incentivized snowball sampling (ISS) are two sampling methods that are commonly used to reach people who inject drugs (PWID). Methods: We generated a set of simulated RDS samples on an actual sociometric ISS sample of PWID in Vilnius, Lithuania ("original sample") to assess if the simulated RDS estimates were statistically significantly different from the original ISS sample prevalences for HIV (9.8%), Hepatitis A (43.6%), Hepatitis B (Anti-HBc 43.9% and HBsAg 3.4%), Hepatitis C (87.5%), syphilis (6.8%) and Chlamydia (8.8%) infections and for selected behavioral risk characteristics. Results: The original sample consisted of a large component of 249 people (83% of the sample) and 13 smaller components with 1-12 individuals. Generally, as long as all seeds were recruited from the large component of the original sample, the simulation samples simply recreated the large component. There were no significant differences between the large component and the entire original sample for the characteristics of interest. Altogether 99.2% of 360 simulation sample point estimates were within the confidence interval of the original prevalence values for the characteristics of interest. Conclusions: When population characteristics are reflected in large network components that dominate the population, RDS and ISS may produce samples that have statistically non-different prevalence values, even though some isolated network components may be under-sampled and/or statistically significantly different from the main groups. This so-called "strudel effect" is discussed in the paper.

    Original languageEnglish
    Pages (from-to)71-77
    Number of pages7
    JournalDrug and Alcohol Dependence
    Volume135
    Issue number1
    DOIs
    Publication statusPublished - 2014

    Fingerprint

    Sampling
    Lithuania
    Chlamydia Infections
    Hepatitis A
    Network components
    Population Characteristics
    Syphilis
    Hepatitis C
    Hepatitis B Surface Antigens
    Hepatitis B
    Pharmaceutical Preparations
    Seeds
    HIV
    Confidence Intervals
    Surveys and Questionnaires
    Population
    Seed

    Keywords

    • Incentivized snowball sampling
    • People who inject drugs
    • Prevalence estimates
    • Respondent driven sampling
    • Sampling methodology
    • Simulations

    ASJC Scopus subject areas

    • Psychiatry and Mental health
    • Toxicology
    • Pharmacology
    • Pharmacology (medical)

    Cite this

    A simulative comparison of respondent driven sampling with incentivized snowball sampling - The "strudel effect". / Gyarmathy, V. Anna; Johnston, Lisa G.; Caplinskiene, Irma; Caplinskas, Saulius; Latkin, Carl A.

    In: Drug and Alcohol Dependence, Vol. 135, No. 1, 2014, p. 71-77.

    Research output: Contribution to journalArticle

    Gyarmathy, V. Anna ; Johnston, Lisa G. ; Caplinskiene, Irma ; Caplinskas, Saulius ; Latkin, Carl A. / A simulative comparison of respondent driven sampling with incentivized snowball sampling - The "strudel effect". In: Drug and Alcohol Dependence. 2014 ; Vol. 135, No. 1. pp. 71-77.
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    abstract = "Background: Respondent driven sampling (RDS) and incentivized snowball sampling (ISS) are two sampling methods that are commonly used to reach people who inject drugs (PWID). Methods: We generated a set of simulated RDS samples on an actual sociometric ISS sample of PWID in Vilnius, Lithuania ({"}original sample{"}) to assess if the simulated RDS estimates were statistically significantly different from the original ISS sample prevalences for HIV (9.8{\%}), Hepatitis A (43.6{\%}), Hepatitis B (Anti-HBc 43.9{\%} and HBsAg 3.4{\%}), Hepatitis C (87.5{\%}), syphilis (6.8{\%}) and Chlamydia (8.8{\%}) infections and for selected behavioral risk characteristics. Results: The original sample consisted of a large component of 249 people (83{\%} of the sample) and 13 smaller components with 1-12 individuals. Generally, as long as all seeds were recruited from the large component of the original sample, the simulation samples simply recreated the large component. There were no significant differences between the large component and the entire original sample for the characteristics of interest. Altogether 99.2{\%} of 360 simulation sample point estimates were within the confidence interval of the original prevalence values for the characteristics of interest. Conclusions: When population characteristics are reflected in large network components that dominate the population, RDS and ISS may produce samples that have statistically non-different prevalence values, even though some isolated network components may be under-sampled and/or statistically significantly different from the main groups. This so-called {"}strudel effect{"} is discussed in the paper.",
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    AU - Caplinskas, Saulius

    AU - Latkin, Carl A.

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