NBME 24 0.05 < p < 1.0 (NBME Answers)

NBME 24 Answers

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A cohort study is done to evaluate the ...
0.05 < p < 1.0 🔍 / 📺 / 🌳 / 📖
tags: biostats

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submitted by stapes2big(16)

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I’m not sure about this one but the way I thought about it was that since the confidence interval included 1, it was not significant. And thus p value must be above 0.05

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tea-cats-biscuits That makes sense! +

asapdoc Had the same reasoning +24

jkan I get that it's not significant, but why is it 0.05<p<1 and not p>1.0 +12

jkan nvm, it's can't be greater than 1 because then it would have a negative% confidence interval which cannot happen (Think if p>0.05 means at least 95% within confidence interval) +12

charcot_bouchard p=0.05 means theres 5% chance null hypothesis is true. p=1 means theres 100% chance null hypothesis is true. >1 means >100% chance which isnt possible. +14

wowo p is a probability, so can't be greater than 1 +11

noname @charcot_bouchard, that is not a good interpretation of p-value. A better interpretation of p=0.05 would be: If in reality there is no increase in risk (RR=1), and if we replicated the same study of the same sample size many different times, then we would expect to find a risk ratio of (X) only about 5% of the time. +2

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submitted by ∗potentialdoctor1(41)

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p-value refers to the probability of making a type I error (probability of having a false positive). When the 95% confidence interval does not include the null value (1 for ratio, 0 for difference), 0 < p < 0.05 (between 0% and 5% chance of having a false positive). However, when the 95% confidence interval includes the null value, 0.05 < p < 1.0 (between 5% and 100% chance of having a false positive).

Think of it as follows ---> If the 95% confidence interval includes the null value, then you have somewhere between 5% and 100% chance of being wrong if you conclude it is right. Conversely, if the 95% confidence interval does not include the null value, then you have between 0% and 5% chance of being wrong if you conclude that is is right

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drippinranch Excellent explanation! +3

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submitted by ∗abhishek021196(119)

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Null (H 0 ) Hypothesis = Hypothesis of no difference or relationship (eg, there is no association between the disease and the risk factor in the population).

If the 95% CI for odds ratio or relative risk includes 1, H 0 is not rejected.

Since the CI here includes 1, it means that its not significant and therefore p value should not be < 0.5. Therefore p = 0.5-1.

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submitted by ∗susyars(41)

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Maybe I'm just too stupid to understand the arrows, because everytime i look at them i have a headache

I just cant

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susyars Brainfart here: I understand the null hypothesis and the null value yada yada But all those >/< arrows drove me crazy If youre struggling like me, because you couldnt find where the freaking p is greater than 0.05 (0.05 < p < 1) heres a drawing to make you understand with apples and pears https://cdn.discordapp.com/attachments/676273979329347584/683142094868578371/unknown.png we are talking about a value between 0 and 1 where 1 is the 100% 95% of CI is where most of your samples will fall 5% (0.05) is the rest (null value) from 0 to 0.05 which is a really small number •Everything that falls between 0-0.05 is the null value •p must be lesser than 0.05 (0.04 0.03 0.02) but greater than 0 (thats why 0 cant be the answer Everything that falls between 0.05 (5%) and 1 (100%) is greater than p which makes your test not good (but we dont call it good or bad test, we say significant or no significant because is more fancy) Thats why p cannot be > 1 +3

corgilobacter https://discord.gg/sn3HvjA https://cdn.discordapp.com/attachments/676273979329347584/683142094868578371/unknown.png https://cdn.discordapp.com/attachments/676273979329347584/683143442536464517/unknown.png Wellsaid Susy!!! you helped me understand this! You're the bestest! +

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submitted by ∗dyckim4(4)

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wait according to B&B CL including 0 is very similar to saying P>0.05. I am confused now

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