P-values e.g

P-values e.g

1. 1. using an RCT as an example to demonstrate hypothesis testing

   • Imagine an RCT is conducted to compare two treatments
     • an active drug for Irritable Bowel Syndrome (IBS
     • and a placebo
     • All conditions are identical apart from distribution of the actual drug to the intervention group, and the placebo to the control group.
   • it is reasonable for the null and alternative hypotheses to state:
     • 1. H0 = the mean (ie IBS ‘score’) of the two groups are not different
     • 2. H1 = the mean (ie IBS ‘score’) of the two groups are statistically significantly different
     • The p-value determines whether we accept or reject the null hypothesis.

2. 2.researchers need to statistically demonstrate that the difference obtained between the effect of the drug for IBS compared.

   • that of the placebo is either due to chance, or that a statistically significant difference actually exists.
   • the null hypothesis (no difference) can be ruled out,
     • then the differences between the drug and placebo is most likely due to the effectiveness of the drug itself.
   • A
     • The researchers decide what significance level to use
       • what cut-off point will decide significance in the test they use (in this case the cut off for the p-value)
         • The most commonly used level of significance is 0.05.
           • any test resulting in a p-value equal to, or less than 0.05 would be significant.
             • would reject the null hypothesis in favour of the alternative hypothesis
   • B
     • P-values equal to or less than 0.05
       • suggest that the observed associations could be found by chance in 5 out of 100 samples
         • That is, the results of 5 in 100 samples are due to chance occurrence.

3. GOLDEN RULES

   • We can REJECT the null hypothesis if p ≤ 0.05.
   • We must ACCEPT the null hypothesis if p > 0.05.

4. do not simply provide you with a “Yes” or “No” answer

   • provide a sense of the strength of the evidence against the null hypothesis

5. lower the p-value, the stronger the evidence

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