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

Multiple Comparison Tests01:13

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
Multiple Regression01:25

Multiple Regression

Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Longitudinal Studies01:26

Longitudinal Studies

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...

You might also read

Related Articles

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

Sort by
Same author

Evidence for Evidence-Based Medicine - A Call for Some Theory and a New Problem.

NEJM evidence·2026
Same author

Age-Friendly Health System Implementation in Outpatient Settings: A Systematic Review.

Journal of the American Geriatrics Society·2026
Same author

Differences in Bladder Cancer Diagnosis by Demographic Factors: A Simulation Modeling Analysis.

medRxiv : the preprint server for health sciences·2026
Same author

Understanding Bladder Cancer Screening Limits Through Comparative Modeling: The Maximum Clinical Incidence Reduction (MCLIR) Methodology.

medRxiv : the preprint server for health sciences·2026
Same author

Fiber intake and laxation in people with normal bowel function: a systematic review.

The American journal of clinical nutrition·2026
Same author

On Representations and Quantifications of Uncertainty.

Medical decision making : an international journal of the Society for Medical Decision Making·2026

Related Experiment Video

Updated: May 19, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials
08:36

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

Published on: April 19, 2024

Meta-analysis of effect sizes reported at multiple time points: a multivariate approach.

Thomas A Trikalinos1, Ingram Olkin

  • 1Center for Evidence-based Medicine, Brown University, Providence, RI 02912, USA. thomas_trikalinos@brown.edu

Clinical Trials (London, England)
|August 9, 2012
PubMed
Summary

This study introduces a multivariate meta-analysis approach to effectively analyze correlated data from multiple time points, offering a more comprehensive alternative to separate analyses.

Related Experiment Videos

Last Updated: May 19, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials
08:36

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

Published on: April 19, 2024

Area of Science:

  • Biostatistics
  • Medical Research Methodology
  • Quantitative Synthesis

Background:

  • Comparative studies often report results at multiple time points.
  • Correlated data from the same patients are typically analyzed separately at each time point, ignoring temporal dependencies.
  • This univariate approach leads to a loss of statistical power and potentially biased estimates.

Purpose of the Study:

  • To develop a novel meta-analytic framework for estimating treatment effects across successive time points.
  • To incorporate stochastic dependencies between effect sizes at different time points within a multivariate model.
  • To provide a more accurate and efficient quantitative synthesis of longitudinal data.

Main Methods:

  • Development of fixed and random effects models for multivariate meta-analysis of longitudinal data.
  • Formulation of covariance and correlation calculations for common effect size metrics (log odds ratio, log risk ratio, risk difference, arcsine difference).
  • Application to a meta-analysis of 17 trials on adjuvant cancer therapy, assessing survival at 6, 12, 18, and 24 months.

Main Results:

  • Comparison of univariate meta-analyses with the proposed joint multivariate analyses.
  • Demonstration of minor differences in effect size magnitudes and standard errors between the two approaches.
  • Exploration of conditional multivariate analyses for examining treatment effects at later time points based on earlier observations.

Conclusions:

  • Multivariate methods offer an efficient and attractive approach for analyzing data reported at multiple time points.
  • These methods can serve as a valuable complement or alternative to traditional separate meta-analyses.
  • Further simulation and empirical studies are recommended to fully elucidate the benefits of multivariate analyses.