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Related Concept Videos

Convenience Sampling Method00:55

Convenience Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
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Cluster Sampling Method01:20

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Systematic Sampling Method01:17

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Stratified Sampling Method01:16

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Random Sampling Method01:09

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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Surveys02:16

Surveys

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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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Comparing snowball sampling and RDS: A methodology and case study.

Dongah Kim1, Krista J Gile2, Bradley Mathers3

  • 1Integrative Biology Department, University of Texas Austin, Austin, Texas, United States of America.

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|January 14, 2026
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Summary
This summary is machine-generated.

Respondent Driven Sampling (RDS) and snowball sampling are methods for reaching hard-to-reach populations. This study simulates their use in bio-behavioral surveys to compare their effectiveness and identify when simpler methods are appropriate.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Hard-to-reach populations often require specialized sampling techniques for effective public health surveillance.
  • Respondent Driven Sampling (RDS) is a probability-based method recommended for bio-behavioral surveys (BBS) of HIV, viral hepatitis, and STIs.
  • Traditional snowball sampling is often used non-probabilistically, and simplified versions are being developed for resource-limited settings.

Purpose of the Study:

  • To compare the outcomes of snowball sampling initiated from a health service with Respondent Driven Sampling (RDS) using data-based simulations.
  • To evaluate the similarities and differences between these two sampling methodologies in the context of bio-behavioral surveys.
  • To inform the development of simplified rapid bio-behavioral survey methodologies.

Main Methods:

  • Utilized data-based simulations to model sampling processes.
  • Compared results from a simulated snowball sample (recruitment from health services) with a simulated RDS sample.
  • Analyzed potential similarities and differences in population estimates derived from each method.

Main Results:

  • Simulations provide insights into the comparative performance of snowball sampling and RDS.
  • Identified specific scenarios where snowball sampling might approximate RDS outcomes.
  • Highlighted the trade-offs between sampling complexity, cost, and data quality.

Conclusions:

  • Respondent Driven Sampling (RDS) offers advantages for probability-based sampling in bio-behavioral surveys.
  • Simplified snowball sampling methods may be viable alternatives when RDS is infeasible, but require careful consideration.
  • Further research and simulation are needed to refine rapid bio-behavioral survey methodologies for key populations.