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P values are less informative and can be positively misleading

In the current case, we calculate the upper confidence limit as this indicates the worst credible interpretation of the data. Then, the condition for acceptance of the new treatment is that this upper limit does not enter the failure zone starting at +1 mM. As the decision is based solely on this upper limit, a lower limit would have served no useful purpose and was not calculated. [Pg.113]

Notice the difference. For equivalence testing we have to show that any change lies between an upper and a lower limit, but with non-inferiority testing we only have to show that there is no change beyond a single (upper or lower) limit. [Pg.113]

Can we demonstrate that the new product/procedure is at least as good as that with which it is being compared We must be able to show that the most pessimistic onesided confidence limit excludes any adverse difference large enough to be of practical significance. [Pg.113]

All of the above procedures - demonstration that a change is large enough to be of practical significance or demonstration of equivalence or non-inferiority - are entirely dependent upon the use of the 95 per cent Cl for the size of the treatment effect. P values would be pointless (unless we wanted to cheat ). [Pg.113]

However, P values are not only less informative than the 95 per cent Cl they can even be downright misleading, if taken in isolation. Table 9.2 gives the results of two trials of candidate antipyretic drugs (A and B). A beneficial effect would consist of a reduction in temperature and clinical judgement is that a reduction of at least 0.5°C would be required for patients to feel any benefit. It is also assumed that a rise of 0.5°C would be detrimental. [Pg.113]


See other pages where P values are less informative and can be positively misleading is mentioned: [Pg.113]    [Pg.113]   


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