In practice, however, it is not always feasible to employ this approach, for instance when participants need to undergo group therapy in groups of size 20. This is the same with the full sequential method, but here one can also stop when it is sufficiently clear that H 0 will not be rejected. In interim analysis, one can stop data collection early in case there is sufficient evidence to reject H 0. Statistically, this is the optimal approach of deciding upon the sample size. The computation of this log-likelihood ratio is far from straightforward. Wald’s procedure, for instance, involves computing the cumulative log-likelihood ratio after each observation, and stopping when this sum leaves a pre-specified interval ( a, b). These sequential approaches are more technical than standard methods. Theories about this by Abraham Wald 14 and Alan Turing 19, 20 date back to the 1940s. In full sequential approaches, one doesn’t check the data at a few pre-specified points, but after every observation. The Bonferroni-correction, and other corrections, ensure that this so-called familywise error rate remains at an acceptable level. When, for instance, performing 10 independent tests, whilst H 0 is true, then the probability of finding at least one false positive is equal to 1 – (1 − 0.05) 10 = 40.13%, very high. This 5% is something many scientists think is an acceptably small probability for incorrectly rejecting the null hypothesis (although you can make a motivated choice for another rate 8, 9). If the null hypothesis holds true, a single statistical test will yield a false positive, so p < 0.05, in 5% of the times. Corrections such as the Bonferroni-correction are included in most statistical textbooks. In this scenario, due to a large number of statistical tests being performed, the number of false-positives is increased and this needs to be corrected for (Fig. The problem with multiple statistical testing is more often recognized in the context of multiple independent testing.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |