| Combining Statistical Tests By Multiplying p-values (2007) | |||||||||||||
Abstract | |||||||||||||
| A general discussion on combining statistical hypothesis tests is followed by an application involving point source detection in skymaps. The traditional literature on combining statistical tests has concentrated on a regime in which p-values as large as 0.05 are still of interest, and in which it is dangerous to treat tests as truly independent. But for point source detection, very small p-values are desired, and situations can arise in which one can fairly assume independence of the tests. 1. Introduction Classical hypothesis testing requires that both the null hypothesis H o and the desired "level" ff be specified beforehand, before ever looking at the data. Then a statistic is computed on the data, and this statistic is converted to a p-value. If the p-value is less than ff, then the hypothesis is rejected. The level ff is also the false alarm rate: if the the null hypothesis is true, and assuming that the test is well-calibrated, then it will be rejected with probability ff. I... | |||||||||||||
Publication details | |||||||||||||
| |||||||||||||