The Vote Counting Trap
Why 50% of ‘Failed’ Studies Are Actually Successes
The Intuition Fail
Imagine you read 10 studies on a new depression treatment. * 5 studies find a significant effect (\(p < .05\)). * 5 studies find no significant effect.
Conclusion? Most people say: “The results are inconsistent. We need more research.”
The Truth: This is exactly what perfect consistency looks like.
The Simulation
Everything below is a computer simulation of identical studies drawn from the exact same population. * True Effect Size: \(\rho = 0.22\) (Medium) * Sample Size: \(N = 68\) (Typical Psychology Study)
Click “Run Code” to see what happens when you run 21 identical studies.
The Lesson
In this simulation, the “Truth” never changed. The only thing that changed was the random noise of sampling.
If you rely on Vote Counting (tallying significant vs non-significant results), you will reject effective treatments 50% of the time.
Meta-Analysis solves this. It ignores the binary “Significance” labels and averages the effect sizes (the dots) to find the invisible line of Truth.