Core idea
Meta-analysis combines effect estimates from multiple studies to obtain a pooled estimate. Study weights are often based on precision (inverse variance). Random-effects models allow true effects to vary across studies.
Interactive: toy forest plot
Adjust heterogeneity and see how study effects spread. This is a visualization tool (not a full statistical implementation).
Forest-style display
Dots: study effects. Horizontal lines: approximate CIs.
Real Dental Scenario
Fluoride Varnish vs Placebo for Caries Prevention
Six randomized controlled trials examined whether fluoride varnish applied biannually reduces new carious lesions compared to placebo in children aged 6-12. Below are realistic study-level results using the standardized mean difference (SMD) in DMFS increment (negative values favor fluoride varnish).
| Study | N | SMD | 95% CI | Weight |
|---|
Animated Forest Plot: Fluoride Varnish Efficacy
Heterogeneity Assessment
Clinical Interpretation
Results will appear after the forest plot is built.
Dental example
Pooling clinical trials on fluoride varnish efficacy, implant survival comparisons, or periodontal therapy outcomes often uses meta-analysis. Always report heterogeneity and evaluate bias (e.g., funnel plots) in real studies.