Related Experiment Video
Updated: Apr 28, 2026
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
14.3K
Systematic review of methods for individual patient data meta- analysis with binary outcomes
Doneal Thomas, Sanyath Radji, Andrea Benedetti1
1Department of Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, Canada. andrea.benedetti@mcgill.ca.
BMC Medical Research Methodology
|June 20, 2014
Summary
Individual patient data meta-analyses (IPD-MA) for binary outcomes are increasing. Random effects logistic regression is common, but methods reporting needs improvement, despite heterogeneity being discussed.
Area of Science:
- Biostatistics
- Clinical Epidemiology
- Health Services Research
Background:
- Individual patient data meta-analyses (IPD-MA) are the gold standard, offering advantages over summary statistics.
- The use of binary outcomes in IPD-MA has increased significantly since 1999-2001.
- Previous reviews indicated insufficient reporting of statistical methods in IPD-MA.
Purpose of the Study:
- To explore statistical methods used in IPD-MA of binary outcomes.
- To assess the reporting completeness of statistical approaches in recent IPD-MA.
- To identify trends in the analysis of binary outcomes in IPD-MA.
Main Methods:
- Systematic review of 26 individual patient data meta-analyses (IPD-MA) published in 2011 with binary outcomes.
- Analysis focused on study goals, data acquisition, statistical approaches (one-stage vs. two-stage), and effect modeling (fixed vs. random effects).
- Investigation of heterogeneity assessment and covariate effect analysis.
Main Results:
- 19 of 26 IPD-MA employed a one-stage analysis approach.
- Nine IPD-MA utilized a one-stage random treatment-effect logistic regression model.
- While heterogeneity was discussed in most studies, detailed reporting of methods remains a concern.
Conclusions:
- Binary outcomes are increasingly prevalent in IPD-MA.
- Random effects logistic regression is the most common analytical method for binary outcomes in IPD-MA.
- Despite advancements, detailed reporting of statistical methods in IPD-MA requires further improvement.
Related Concept Videos
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
627
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
627
01:24Kaplan-Meier Approach
788
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
788
01:12Analysis of Population Pharmacokinetic Data
992
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
992
01:20Comparing the Survival Analysis of Two or More Groups
710
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...
710
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
359
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
359
01:20Study Designs in Epidemiology
1.6K
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
1.6K