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 Experiment Videos

A technique for summarizing longitudinal data

D K Hathaway1, R B D'Agostino

  • 1Department of Mathematics, Olivet Nazarene University, Kankakee, IL 60901-0592.

Statistics in Medicine
|December 15, 1993
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Utilization of absolute monocyte counts to predict cardiovascular events in people living with HIV.

HIV medicine·2020
Same author

Extraskeletal Calcifications in Hutchinson-Gilford Progeria Syndrome.

Bone·2019
Same author

Transfer from paediatric to adult care for young adults with Type 2 diabetes: the SEARCH for Diabetes in Youth Study.

Diabetic medicine : a journal of the British Diabetic Association·2018
Same author

Pepsin in saliva as a biomarker for oropharyngeal reflux compared with 24-hour esophageal impedance/pH monitoring in pediatric patients.

Neurogastroenterology and motility·2016
Same author

Plasminogen activator inhibitor and the risk of cardiovascular disease: The Framingham Heart Study.

Thrombosis research·2016
Same author

Pre-transplant predictors of one yr weight gain after kidney transplantation.

Clinical transplantation·2014
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
Same journal

Moving From Individualized Risk-Based Prevention to Benefit-Based Prevention: Estimating Individualized Life-Years Gained From Prevention Services as a Basis for Eligibility.

Statistics in medicine·2026
See all related articles

Researchers developed a method to efficiently summarize longitudinal data using four key statistics and time. This approach simplifies complex data analysis and improves result interpretation for studies like the Framingham Heart Study.

Area of Science:

  • Biostatistics
  • Longitudinal Data Analysis

Background:

  • Many scientific studies generate longitudinal data, tracking subjects over time.
  • Existing methods often fail to utilize this data efficiently, leading to potential loss of valuable information.

Purpose of the Study:

  • To propose a novel technique for reducing longitudinal data into a manageable set of summary statistics.
  • To demonstrate the utility of these derived statistics in subsequent analyses, such as regression.

Main Methods:

  • Developed a mathematical approach to derive four common summary statistics from longitudinal data.
  • These statistics, along with time, serve as a reduced dataset for further analysis.
  • Applied the technique to data from the Framingham Heart Study for illustration.

Related Experiment Videos

Main Results:

  • The proposed method effectively reduces complex longitudinal datasets into interpretable summary statistics.
  • Using these statistics simplifies subsequent analyses and enhances the clarity of results.
  • The technique provides a mathematically justified alternative to arbitrary data summarization.

Conclusions:

  • This technique offers an efficient and interpretable way to handle longitudinal data.
  • It enables more effective use of collected data in various statistical analyses.
  • The method has broad applicability in research involving repeated measures over time.