Comment on WHAT IF WHAT IF

LodeMike@lemmy.today ⁨2⁩ ⁨days⁩ ago

• TropicalDingdong@lemmy.world ⁨2⁩ ⁨days⁩ ago

  Z value (also known as z-score) is the distance (signed) between your model and a prediction.

  If your model is a mean (the average), the z-scores are the set of differences between the mean and the values used to compose the mean.

  If your model is a regression (relating, say, two variables relating x and y), then the z-score is the difference between the regression line and the values used to fit the regression.

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• whosepoopisonmybuttocks@sh.itjust.works ⁨2⁩ ⁨days⁩ ago

  My limited knowledge on this subject: The z-score is how many standard deviations you are from the mean.

  In statistical analysis, things are often evaluated against a p (probability) of 0.05 (or 5%), which also corresponds to a z-score of 1.96 (or roughly 2).

  So, when you’re looking at your data, things with a z score >2 or <2 would correspond to findings that are “statistically significant,” in that you’re at least 95% sure that your findings aren’t due to random chance.

  As others here have pointed out, z-scores closer to 0 would correspond to findings where they couldn’t be confident that whatever was being tested was any different than the control, akin to a boring paper which wouldn’t be published. "We tried some stuff but idk, didn’t seem to make a difference.*

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  • Passerby6497@lemmy.world ⁨2⁩ ⁨days⁩ ago

    But it could also make for an interesting paper, “We tried putting healing crystals above cancer patients but it didn’t seem to make any difference.”

    But then you have competing bad outcomes:

    1. The cancer patients aren’t given any other treatment, so you’re effectively harming them through lack of action/treatment
    2. The cancer patients are given other (likely real) treatments, meaning your paper is absolutely meaningless

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    • whosepoopisonmybuttocks@sh.itjust.works ⁨1⁩ ⁨day⁩ ago

      There’s certainly a lot to discuss, relative to experimental design and ethics. Peer review and good design hopefully minimizes the clearly undesirable scenarios you describe as well as other subtle sources of error.

      I was really just trying to explain what we’re looking at on op’s graph.

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    • tias@discuss.tchncs.de ⁨1⁩ ⁨day⁩ ago

      Some people will refuse other treatments regardless, so you’re not changing the outcome.

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  • HeyThisIsntTheYMCA@lemmy.world ⁨1⁩ ⁨day⁩ ago

    i’m in a couple “we tried some stuff but it really didn’t work” medical “research” papers, which we published so no one would try the same thing again.

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• marcos@lemmy.world ⁨2⁩ ⁨days⁩ ago

  As I understand it, the data there is the histogram of z-value observed by some census of published papers.

  They should make a normal curve, but the publishing process is biased.

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  • Squirrelsdrivemenuts@lemmy.world ⁨2⁩ ⁨days⁩ ago

    But we also prioritize research where we suspect/hypothesize differences, so I think even if all research was published it wouldn’t necessarily be a normal distribution.

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• ivanafterall@lemmy.world ⁨2⁩ ⁨days⁩ ago

  A Z score is a type of airplane, I believe.

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• iAvicenna@lemmy.world ⁨2⁩ ⁨days⁩ ago

  I came here with the same question but now I realize that if I ask it I will only get replies explaining me what Z-score is and not Z-score of what. So I will just assume it is sth akin to h-index. Still does not make much sense to me as to why average h-index papers “don’t survive” (i.e get rejected because no one is interested lets say) where as negative ones do.

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