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

Systematic Sampling Method01:17

Systematic Sampling Method

10.3K
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.
Systematic sampling is one of the simplest methods...
10.3K
Sampling Plans01:23

Sampling Plans

1.4K
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...
1.4K
Stratified Sampling Method01:16

Stratified Sampling Method

11.7K
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...
11.7K
Cluster Sampling Method01:20

Cluster Sampling Method

11.0K
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.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.0K
Sampling Methods: Overview01:06

Sampling Methods: Overview

3.7K
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
3.7K
Data Collection by Observations01:08

Data Collection by Observations

11.0K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
11.0K

You might also read

Related Articles

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

Sort by
Same author

Sparse Canonical Correlation Analysis for Multiple Measurements With Latent Trajectories.

Biometrical journal. Biometrische Zeitschrift·2025
Same author

Estimating overall survival of glioblastoma patients using clinical variables, tumor size, and location.

Neuro-oncology advances·2025
Same author

Identifying Predictors for Heart Failure Outcomes in Phospholamban p.(Arg14del)-Positive Individuals.

JACC. Heart failure·2025
Same author

Application of image guided analyses to monitor fecal microbial composition and diversity in a human cohort.

Scientific reports·2025
Same author

Aortic Function in a Longitudinal 4D Flow MRI Study in Marfan Syndrome Patients Receiving Resveratrol.

Journal of magnetic resonance imaging : JMRI·2025
Same author

Cohort Profile Update: The Healthy Life in an Urban Setting (HELIUS) Study.

International journal of epidemiology·2025
Same journal

Methods for incorporating test result information within the high-dimensional propensity score framework: application in UK electronic health record data.

BMC medical research methodology·2026
Same journal

Sparse multi-way DMDC for longitudinal classification in high dimension low sample size data.

BMC medical research methodology·2026
Same journal

Tree-based exploratory identification of predictive biomarkers in non-randomized data.

BMC medical research methodology·2026
Same journal

Comparative evaluation of interrupted time series analytical methods for healthcare quality improvement research: a Monte Carlo simulation study.

BMC medical research methodology·2026
Same journal

Methodological advances in claims-based dementia algorithms: integrating medication and clinical data for medicare populations.

BMC medical research methodology·2026
Same journal

An interpretable XGboost algorithm for predicting 30-day mortality in acute pancreatitis using routine biomarkers.

BMC medical research methodology·2026
See all related articles

Related Experiment Video

Updated: Apr 27, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.3K

Adaptive list sequential sampling method for population-based observational studies.

Michel H Hof1, Anita C J Ravelli, Aeilko H Zwinderman

  • 1Department of Clinical Epidemiology, Bioinformatics, and Biostatistics, Academic Medical Center - University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands. m.h.hof@amc.uva.nl.

BMC Medical Research Methodology
|June 27, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive sampling method to improve participant recruitment in observational studies. The method effectively recruits samples with desired compositions, even with unknown participation rates and delayed responses.

More Related Videos

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

2.5K
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

1.2K

Related Experiment Videos

Last Updated: Apr 27, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.3K
Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

2.5K
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

1.2K

Area of Science:

  • Epidemiology
  • Biostatistics
  • Health Services Research

Background:

  • Participant recruitment in population-based observational studies faces challenges like non-participation and delayed responses.
  • These issues can lead to biased sample composition, affecting study costs and precision.
  • Limited prior information on willingness to participate hinders proactive recruitment adjustments.

Purpose of the Study:

  • To develop and evaluate a novel sampling method to address recruitment challenges in observational studies.
  • To enable precise sample composition control despite unknown participation probabilities and delayed responses.

Main Methods:

  • An adaptive list sequential sampling method was developed.
  • The method sequentially evaluates individuals for invitation, adjusting for estimated participation probabilities.
  • It utilizes data from previously invited individuals to refine participation probability estimates.

Main Results:

  • Simulations demonstrated the method's ability to estimate participation probabilities during recruitment.
  • The adaptive sampling approach successfully recruited samples with a predefined specific composition.

Conclusions:

  • The adaptive list sequential sampling method is effective for recruiting samples with desired compositions.
  • It is particularly useful when prior information on participation willingness is limited or individuals respond with delays.