Related Experiment Video
Updated: Apr 28, 2026
08:36
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
Published on: April 19, 2024
1.4K
Likelihood-Based Random-Effect Meta-Analysis of Binary Events
Anup Amatya1, Dulal K Bhaumik, Sharon-Lise Normand
1a Department of Health Sciences , New Mexico State University , Las Cruces , New Mexico , USA.
Journal of Biopharmaceutical Statistics
|June 12, 2014
Summary
Moment-based meta-analysis methods may be inaccurate, especially for rare binary outcomes. Likelihood-based mixed-effects models offer a more accurate alternative for evaluating medical intervention efficacy and safety.
Area of Science:
- Biostatistics
- Medical Research Methodology
- Evidence Synthesis
Background:
- Meta-analysis is crucial for assessing medical intervention efficacy and safety.
- Traditional moment-based meta-analytic methods face accuracy challenges, particularly with rare binary outcomes and heterogeneous effect sizes.
Purpose of the Study:
- To compare likelihood-based mixed-effects modeling strategies against traditional moment-based methods in meta-analysis.
- To evaluate the performance of different mixed-effects models for binary outcomes, focusing on estimation and testing of overall effect and heterogeneity.
Main Methods:
- Comparative analysis of various mixed-effects modeling strategies.
- Evaluation of model performance using metrics such as bias, type I error rate, and type II error rate.
- Focus on meta-analysis of studies with binary outcomes.
Main Results:
- Models allowing heterogeneity in both baseline rate and treatment effect demonstrated superior performance.
- These advanced models exhibited lower type I and type II error rates.
- Estimates derived from these models were found to be the least biased among those considered.
Conclusions:
- Likelihood-based mixed-effects modeling, particularly models accommodating heterogeneity in baseline rates and treatment effects, provides a more accurate and reliable approach for meta-analysis.
- These methods offer improved estimation and testing for overall effects and heterogeneity, especially for binary outcomes.
More Related Videos
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
14.3K
04:35Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
2.9K
Related Concept Videos
01:09Odds Ratio
2.3K
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
2.3K
01:13Randomized Experiments
6.3K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
6.3K
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
01:20Comparing the Survival Analysis of Two or More Groups
712
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...
712
01:52Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
01:12Hazard Ratio
754
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
For example, in a clinical trial...
754