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If the drug was not effective, there was a 3.3% probability of concluding that it was (type I alpha error).
If the drug was effective, there was a 14.2% probability of concluding that it was not (type II beta error).
The probability of concluding H 2 ⋆ is higher under BHT-A, BMA, and BIT.
† Size is the probability of concluding that the true slope is not zero when in fact it is zero, and power is the probability of concluding that the true slope is not zero when in fact it is not zero.
If the therapy is actually not promising, there is a 0.049 probability of concluding that it is (the target significance level was set to 5%).
If the therapy is actually promising, there is a 0.198 probability of concluding that it is not (the target for this value was set to 20%).
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The probability of erroneously concluding that the new treatment is active (P⩾0.20) when it is actually ineffective (P⩽0.04) is <0.05.
The probability of erroneously concluding that the treatment is ineffective (P<0.20) when is actually effective (P⩽0.04) is <0.05.
If the null hypothesis is true, then the probability of erroneously concluding that the therapy is sufficiently promising (type I error) was limited to 5%.
A 5 % level of significance was used with the caveat that there were multiple comparisons, which increased the chance of a Type I error, i.e. the probability of erroneously concluding that there was an effect of the IDCAP interventions.
Bonferroni correction was utilized to adjust for multiple comparisons in the SNP analysis resulting in a corrected significance level of p < 0.004 to give a 95% probability of correctly concluding not to reject the null hypothesis in the χ test.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com