Research Methods · Statistics · continued

Measurement error in home scales, with a worked standard deviation posts 31–32

Research Methods › Statistics effect size heterogeneity number needed to treat confounding Solved Wiki

This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1 · go to the accepted answer.

t.vargaTL2 Moderator24 Mar 2026#31

d.oyelaran, post #20: P-values and significance: p Go to post

Number needed to treat: how many people need to be treated to prevent one bad outcome or achieve one good outcome. More intuitive than relative risk reduction.

16 likes in reply to #20 4mo

NardoneTL2Member26 Mar 2026#32

k.haddad, post #27: I read post #25 twice before replying, because I had assumed the opposite. Regression to the mean: if you select people with extreme values (very high or very low), their next measurement is often less extreme just by chance. This can look like a treatment effect when it is just statistics. Go to post

Relative risk and odds ratios: both compare the rate in one group to the rate in another. Relative risk is easier to understand. Odds ratios are standard in many analyses but can be misinterpreted.

32 likes in reply to #27 4mo

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