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

Longitudinal studies with continuous responses.

N M Laird1, C Donnelly, J H Ware

  • 1Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115.

Statistical Methods in Medical Research
|January 1, 1992
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

Cardiac transplant outcomes in a pediatric patient with novel homozygous variants in TOP3Α causing mitochondrial dysfunction.

Molecular genetics and metabolism·2025
Same author

Quality Indicators and Benchmarks for Radiotherapy in Lung Cancer: A Modified Delphi Approach.

Clinical oncology (Royal College of Radiologists (Great Britain))·2025
Same author

High-resolution three-dimensional imaging of topological textures in nanoscale single-diamond networks.

Nature nanotechnology·2024
Same author

Determination of optimal experimental conditions for accurate 3D reconstruction of the magnetization vector via XMCD-PEEM.

Journal of synchrotron radiation·2024
Same author

The role of platelet-rich plasma in androgenetic alopecia: A systematic review.

Journal of cosmetic dermatology·2024
Same author

Social Network Factors Affect Nutrition Risk in Middle-Aged and Older Adults: Results from the Canadian Longitudinal Study on Aging.

The journal of nutrition, health & aging·2023
Same journal

Regression analysis of misclassified current status data with potentially unknown test accuracy.

Statistical methods in medical research·2026
Same journal

Bayesian multivariate linear mixed-effects models with varied association structures.

Statistical methods in medical research·2026
Same journal

Inference about the ratio of age-standardized rates between two overlapping populations.

Statistical methods in medical research·2026
Same journal

A robust neural network with random effects for subject-specific prediction of clustered count data.

Statistical methods in medical research·2026
Same journal

A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints.

Statistical methods in medical research·2026
Same journal

Joint analysis of longitudinal and recurrent event data: A functional regression approach with autoregressive frailty.

Statistical methods in medical research·2026
See all related articles

New statistical methods and software enhance the analysis of longitudinal data, crucial for understanding changes over time in areas like lung function studies. These techniques improve repeated measures and growth curve analyses.

Area of Science:

  • Statistics
  • Biostatistics
  • Longitudinal Data Analysis

Background:

  • Longitudinal studies involve serial measurements, increasingly vital in applied research.
  • Recent advancements have introduced novel analytical techniques and user-friendly computer software.

Purpose of the Study:

  • To review newly developed statistical methods for analyzing longitudinal data.
  • To discuss the application of these methods in various research designs.
  • To highlight available computer packages for implementing these analyses.

Main Methods:

  • Review of advanced statistical techniques for longitudinal data.
  • Application examples including repeated measures, cross-over designs, and growth curve analyses.
  • Evaluation of contemporary statistical software for longitudinal data analysis.

Related Experiment Videos

Main Results:

  • Numerous new methods and software tools are now available for longitudinal data analysis.
  • These methods effectively address standard problems in repeated measures and growth curve modeling.
  • Illustrative examples using lung function data demonstrate practical application.

Conclusions:

  • The reviewed methods offer powerful tools for analyzing complex longitudinal data.
  • Availability of software facilitates the implementation of these advanced statistical techniques.
  • These advancements are expected to enhance the rigor and scope of applied research utilizing longitudinal studies.