Putting together lots of small studies gives a better guess about what's really going on in the whole population than looking at just one small study.
Evidence from Studies
Supporting (5)
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The Resistance Training Dose-Response: Meta-Regressions Exploring the Effects of Weekly Volume and Frequency on Muscle Hypertrophy and Strength Gain
This study combines many small exercise studies into one big analysis, showing that doing so helps find clearer patterns than any single small study could. That supports the idea that combining studies gives better answers.
Repairing Trust in Robots?: A Meta-analysis of HRI Trust Repair Studies with a No-Repair Condition
This study combines many small experiments about robot trust repair into one big analysis, showing that doing so gives a clearer answer than any single small study could. That supports the idea that combining small studies helps us understand the real effect better.
P-value driven methods were underpowered to detect publication bias: analysis of Cochrane review meta-analyses.
The study found that when you combine more studies in a meta-analysis, you're better able to spot problems like publication bias, which can distort results. This supports the idea that combining many small studies gives a more accurate overall picture than looking at just one small study.
Robust inference for the unification of confidence intervals in meta-analysis
The study looks at a better way to combine results from many small studies, which supports the idea that doing so gives a clearer picture than any single small study alone.
The study shows that combining many small studies using special methods gives a better guess of the true effect than any single small study can.
Contradicting (0)
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Gold Standard Evidence Needed
According to GRADE and EBM methodology, here is what ideal scientific evidence would look like to definitively prove or disprove this specific claim, ordered from strongest to weakest evidence.