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

Longitudinal Research02:20

Longitudinal Research

12.5K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.5K
Longitudinal Studies01:26

Longitudinal Studies

248
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
248
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

156
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
156
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

2.3K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
2.3K
Censoring Survival Data01:09

Censoring Survival Data

241
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
241
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

81.5K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
81.5K

You might also read

Related Articles

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

Sort by
Same author

Deployment-Related Respiratory Health: Bridging the Gap between Clinical and Epidemiological Associations and Disease Mechanisms An Official American Thoracic Society Workshop Report.

Annals of the American Thoracic Society·2026
Same author

Early-life exposure to ambient temperature and polycystic ovary syndrome: a nationwide cohort study.

International journal of epidemiology·2026
Same author

Long-Term Exposure to Multiple Environmental Factors and Late-Life Cognitive Decline.

Environmental science & technology·2026
Same author

The relation between household dogs and cats during childhood/adolescence with social role outcomes and loneliness among youth with attention-deficit/hyperactivity disorder.

European child & adolescent psychiatry·2026
Same author

Multi ancestry genome wide association meta analysis of urinary aMT6s levels.

Scientific reports·2026
Same author

The association between PM<sub>2.5</sub> components and cognitive decline: the impact of measurement error correction.

Environmental research·2026
Same journal

A Mixture of Distributed Lag Non-Linear Models to Account for Spatially Heterogeneous Exposure-Lag-Response Associations.

Statistics in medicine·2026
Same journal

Practical Considerations for Gaussian Process Modeling for Causal Inference in Quasi-Experimental Studies With Panel Data.

Statistics in medicine·2026
Same journal

Covariate Adjustment for Wilcoxon Two Sample Statistic and Test.

Statistics in medicine·2026
Same journal

Beyond Fixed Thresholds: Optimizing Summaries of Wearable Device Data via Piecewise Linearization of Quantile Functions.

Statistics in medicine·2026
Same journal

A Causal Framework for Evaluating the Total Effect of Strategies Aiming to Expand Screening and to Improve Outcomes.

Statistics in medicine·2026
Same journal

Causal Effects on Nonterminal Event Time With Application to Antibiotic Usage and Future Resistance.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: Sep 14, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K

Exposure Measurement Error Correction in Longitudinal Studies With Discrete Outcomes.

Ce Yang1, Ning Zhang2, Jiaxuan Li1

  • 1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

Statistics in Medicine
|July 18, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistical method to accurately estimate the health effects of long-term exposure to environmental factors like PM2.5, even when exposure data has measurement errors. The method improves bias reduction and coverage probability in longitudinal studies.

Keywords:
air pollutionanxietygeneralized estimating equationlongitudinal datameasurement error correction

More Related Videos

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.4K
A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
08:33

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Published on: September 4, 2019

7.1K

Related Experiment Videos

Last Updated: Sep 14, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.4K
A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
08:33

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Published on: September 4, 2019

7.1K

Area of Science:

  • Environmental Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Environmental epidemiologists frequently assess time-varying exposure histories' impact on health.
  • Exposure measurements in longitudinal studies often contain errors, complicating accurate effect estimation.
  • Existing methods may yield biased results when dealing with mismeasured exposure histories and discrete health outcomes.

Purpose of the Study:

  • To develop and evaluate a statistical method for unbiased estimation of exposure history function effects in longitudinal studies with measurement error.
  • To address the challenge of time-varying exposure misclassification in discrete outcome studies.
  • To improve the accuracy of estimating chronic exposure effects, such as PM2.5 on anxiety disorders.

Main Methods:

  • Development of a novel estimation method tailored for main study/validation study designs.
  • Exploration of various estimation procedures within the proposed framework.
  • Conducting simulation studies to compare the new method against standard analysis.

Main Results:

  • The proposed method demonstrated significant bias reduction in finite samples.
  • It improved nominal coverage probability compared to standard analysis.
  • Simulations confirmed the method's good performance in handling measurement error.

Conclusions:

  • The new method provides unbiased estimates for the effects of mismeasured exposure history functions in longitudinal studies.
  • Failure to correct for exposure measurement error can lead to underestimation of chronic health risks, e.g., PM2.5's effect on anxiety.
  • This approach is valuable for environmental health research involving complex exposure assessments and discrete outcomes.