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

Stratified Sampling Method01:16

Stratified Sampling Method

16.2K
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...
16.2K
Weighted Mean00:57

Weighted Mean

7.5K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
7.5K
Systematic Sampling Method01:17

Systematic Sampling Method

14.0K
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...
14.0K
Choosing Between z and t Distribution01:25

Choosing Between z and t Distribution

3.8K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
3.8K
Study Design in Statistics01:15

Study Design in Statistics

10.3K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
10.3K
Sampling Plans01:23

Sampling Plans

1.3K
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...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Distinct Metabolomic and Lipidomic Profiles Across Donation after Circulatory Death Recovery Strategies Reveal a Common Signature Associated with Primary Graft Dysfunction.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation·2026
Same author

Predictors of durable viral suppression among people living with HIV (PLHIV) on antiretroviral treatment in Almaty, Kazakhstan.

AIDS care·2026
Same author

Inflammation-Induced Claudin-2 Up-Regulation Limits Pancreatitis Development by Enhancing Pancreatic Ductal Transport.

Gastroenterology·2026
Same author

Investigating the use of generative AI policies among ASPPH member schools and programs of public health.

Frontiers in public health·2026
Same author

FDA Draft Guidance for the Use of Bayesian Methods in Clinical Trials.

JAMA·2026
Same author

Pathfinder: Parallel quasi-Newton variational inference.

Journal of machine learning research : JMLR·2026
Same journal

Latent Class Log-Linear Models for Estimating Diagnostic Test Accuracy Without a Gold Standard: A Simulation Study.

Statistics in medicine·2026
Same journal

Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.

Statistics in medicine·2026
Same journal

Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.

Statistics in medicine·2026
Same journal

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.

Statistics in medicine·2026
Same journal

Optimal Weighted Tests for Replication Studies and the 'Two-Trials Rule' With Multiple Hypotheses.

Statistics in medicine·2026
Same journal

Identifiable Copula-Double-Cox Models: A Fully Parametric Framework for Dependent Right-Censored Survival Data.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: Apr 6, 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

15.5K

Incorporating the sampling design in weighting adjustments for panel attrition.

Qixuan Chen1, Andrew Gelman2,3, Melissa Tracy4

  • 1Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, U.S.A.

Statistics in Medicine
|August 5, 2015
PubMed
Summary
This summary is machine-generated.

Weighting adjustment methods can reduce bias in survey estimates caused by panel attrition. Incorporating design factors like strata and clusters into these methods improves accuracy and weight stability.

Keywords:
CHAID algorithmadjustment cell methoddesign variablesmultilevel modelsresponse propensity weighting

More Related Videos

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

9.9K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.2K

Related Experiment Videos

Last Updated: Apr 6, 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

15.5K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

9.9K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.2K

Area of Science:

  • Survey Methodology
  • Statistical Analysis

Background:

  • Panel attrition, the non-response of participants over time, can introduce significant bias into survey estimates.
  • Traditional weighting adjustment methods may not fully account for complex survey designs.

Purpose of the Study:

  • To review and suggest methods for weighting adjustments that incorporate survey design variables to address panel attrition.
  • To demonstrate the effectiveness of these methods in reducing bias and maintaining weight stability.

Main Methods:

  • Review of existing weighting adjustment techniques for panel attrition.
  • Incorporation of design variables (strata, clusters, baseline weights) into attrition analysis.
  • Utilizing multilevel models and decision tree algorithms (e.g., chi-square automatic interaction detection).
  • Simulation studies to evaluate the performance of proposed methods.

Main Results:

  • Weighting approaches incorporating design factors effectively reduce attrition bias in survey estimates.
  • These methods help maintain stable resulting weights.
  • Simulation results confirm the efficacy of the proposed techniques.

Conclusions:

  • Integrating survey design information into attrition weighting adjustments is crucial for accurate survey estimates.
  • The proposed methods offer practical solutions for analysts dealing with panel attrition in complex surveys.
  • A case study illustrates the application of these techniques in a post-disaster community survey.