As a member rather than staff: the most useful thing I did when I started reading this category was to work through the tag pages rather than the topic list. The topic list shows you what is recent. The tags show you what is settled.
10 likes 9mo
Topic summary
About the Statistics category
This is a generated summary. It shows the 5 most-liked posts from a topic of 9, in their original order, with the accepted answer included where one exists. It is a reading aid and it will miss nuance — the full topic is the record.
s.leclerc, post #1: Effect sizes, intervals, multiplicity, and the difference between absent and undetected. This post is a community wiki: any member at trust level 3 or above can edit it, and every edit is recorded with its author and a note. If the scope described here has drifted from what actually gets posted, edit it rather than starting a topic… Go to post
Confounding: a third variable explains an apparent association. In randomised data, randomisation balances confounders. In observational data, confounders can be adjusted for but unknown ones cannot.
Correct me on the arithmetic if it is wrong; I would rather know.
l.krastev, post #7: 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
A distribution shown is worth ten summary statistics. Where a paper shows individual data points, read those first.
s.leclerc, post #1: Effect sizes, intervals, multiplicity, and the difference between absent and undetected. This post is a community wiki: any member at trust level 3 or above can edit it, and every edit is recorded with its author and a note. If the scope described here has drifted from what actually gets posted, edit it rather than starting a topic… Go to post
Narrowing post #8, because the general version has more than one answer.
Bayesian and frequentist analyses answer different questions and both are legitimate. What matters is that the reader knows which is on offer.
Suggested topics
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Sample size intuition for a personal experiment — does this still hold?
Sample size intuition for a personal experiment — does this still hold? I have a specific reason for asking rather than idle curiosity, and the context is below. Reading back through what has been written…
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Second pass at: Multiplicity when you track fifteen variables
Posting this under the heading it deserves: Second pass at: Multiplicity when you track fifteen variables Everything below is what sits behind that. Two things I would like separated before anyone answers on…
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Multiplicity when you track fifteen variables
Multiplicity when you track fifteen variables — setting out what I have, and where I think it stops being reliable. Asking about multiplicity directly, because I have read four threads on it and each answered…
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What a confidence interval means, from scratch
What a confidence interval means, from scratch — that is the question, and I have not found it answered plainly anywhere I have looked. Asking about confidence interval directly, because I have read four…
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Second pass at: Absence of evidence and evidence of absence
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Related topics — sharing the tags effect size, number needed to treat, heterogeneity
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Comparing the STEP programme populations: who was actually enrolled
Comparing the STEP programme populations: who was actually enrolled Writing it up because I had to work it out twice and would rather nobody else did. Two things I would like separated before anyone answers…
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Triple agonism: additive, synergistic, or neither?
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+71 | 80 | 38k | 11mo |
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Second pass at: What pooling buys you and what it destroys
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+32 | 36 | 19k | 4mo |
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SURMOUNT-4 and what withdrawal data does and does not tell an individual — one year on
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Journal club: STEP 1 and the treatment-policy estimand
Journal club: STEP 1 and the treatment-policy estimand Writing it up because I had to work it out twice and would rather nobody else did. Session topic: STEP 1 ( N Engl J Med , 2021). Please read it before…
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3 | 11k | 9h |