Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Surveys02:16

Surveys

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.
Data Collection by Survey01:07

Data Collection by Survey

The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
Convenience Sampling Method00:55

Convenience Sampling Method

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...
Stratified Sampling Method01:16

Stratified Sampling Method

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.
To choose a stratified sample, divide the population into groups called strata and then take a...
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Response Surface Methodology01:16

Response Surface Methodology

Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A reporting checklist for large language models in behavioural science.

Nature human behaviour·2026
Same author

A Framework for Considering the Value of Race and Ethnicity in Estimating Disease Risk.

Annals of internal medicine·2025
Same author

No news is good news? The declining information value of broadcast news in America.

PloS one·2025
Same author

Automated reminders reduce incarceration for missed court dates: Evidence from a text message experiment.

Science advances·2025
Same author

A simple, statistically robust test of discrimination.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Racial Bias in Clinical and Population Health Algorithms: A Critical Review of Current Debates.

Annual review of public health·2024
Same journal

Tau protein as a regulator of mitochondrial function and dynamics.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

A scalable, dividing cell model for the robust propagation and quantification of human sporadic Creutzfeldt-Jakob disease prions.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Epigenetic regulation of mesenchymal BMP signaling directs postnatal organ innervation.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Single-shot wide-field biochemical imaging at 1 kHz frame rate.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Morphogenesis and topological evolution of a frustrated nematic liquid crystal under confinement.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

B cell-intrinsic CXCR3 drives efficient generation of ectopic pulmonary germinal center responses to influenza A virus infection.

Proceedings of the National Academy of Sciences of the United States of America·2026
See all related articles

Related Experiment Video

Updated: Jun 14, 2026

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers
09:16

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers

Published on: March 14, 2018

Assessing respondent-driven sampling.

Sharad Goel1, Matthew J Salganik

  • 1Microeconomics and Social Systems, Yahoo! Research, 111 West 40th Street, New York, NY 10018, USA. goel@yahoo-inc.com

Proceedings of the National Academy of Sciences of the United States of America
|March 31, 2010
PubMed
Summary
This summary is machine-generated.

Respondent-driven sampling (RDS) is a network-based method for studying hard-to-reach groups. This study found RDS estimates are less accurate and have misleadingly narrow confidence intervals than previously thought.

Related Experiment Videos

Last Updated: Jun 14, 2026

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers
09:16

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers

Published on: March 14, 2018

Area of Science:

  • Epidemiology
  • Social Network Analysis
  • Statistical Methodology

Background:

  • Respondent-driven sampling (RDS) is a widely adopted network-based sampling technique.
  • It is frequently used for public health surveillance in hard-to-reach populations, such as people who inject drugs.
  • Empirical validation of RDS methodology has been limited despite its extensive application.

Purpose of the Study:

  • To empirically assess the accuracy and performance of Respondent-driven sampling (RDS).
  • To investigate the reliability of confidence intervals generated by RDS.
  • To evaluate RDS performance under ideal conditions where theoretical assumptions are met.

Main Methods:

  • Simulating RDS sampling from 85 known, network populations.
  • Analyzing the accuracy of trait estimations across diverse network structures.
  • Assessing the width and reliability of RDS-generated confidence intervals.

Main Results:

  • RDS estimates were found to be substantially less accurate than commonly acknowledged.
  • Reported RDS confidence intervals were misleadingly narrow, overstating precision.
  • High variance, rather than bias, was identified as the primary driver of poor RDS performance.
  • Performance was evaluated under best-case simulation scenarios where RDS assumptions held exactly.

Conclusions:

  • The current practice of Respondent-driven sampling (RDS) may not be suitable for critical public health surveillance.
  • The findings suggest a need for re-evaluation of RDS methodology and its application in epidemiological research.
  • High variance in RDS estimates poses a significant challenge to accurate population trait estimation.