The Claim

Forty-five percent of highly cited meta-analyses in the field of strength and conditioning failed to account for correlated observations, such as multiple performance measures from the same athletes or multiple groups within the same study, resulting in artificially narrow confidence intervals and inflated statistical significance.

Source: With Great Power Comes Great Responsibility: Common Errors in Meta-Analyses and Meta-Regressions in Strength & Conditioning Research

What the research says

Supports is higher

Support is ahead, but a single strong opposing study can change this.

Supports
40score
Challenges
0score

These are independent scores, not a percentage. Higher-grade studies count more, so a single strong opposing study can outweigh several weaker ones.

Description
1 study reviewed
In plain English

A lot of big studies that combine other studies on strength and fitness didn’t properly handle cases where the same people were measured multiple times or when one study had several groups — this made their results look more precise and important than they really were.

See the scientific wording

45% of highly cited meta-analyses in strength and conditioning failed to account for correlated observations, such as multiple performance measures from the same athletes or multiple groups within the same study, leading to artificially narrow confidence intervals and inflated statistical significance.

What the research says

1 study
  1. Study: With Great Power Comes Great Responsibility: Common Errors in Meta-Analyses and Meta-Regressions in Strength & Conditioning Research

    This study checked 20 top science reviews in strength training and found that almost half made a math mistake by not realizing that some data came from the same people or groups, making their results look more certain than they really are — which is exactly what the claim says.

Score breakdown, mechanism chain, raw evidence, ideal studies needed & 1 supporting studies

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