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Controlling Error Rates With Multiple Positively-Dependent Tests, Abdullah Al Masud
Controlling Error Rates With Multiple Positively-Dependent Tests, Abdullah Al Masud
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
It is a typical feature of high dimensional data analysis, for example a microarray study, that a researcher allows thousands of statistical tests at a time. All inferences for the tests are determined using the p-values; a smaller p-value than the α-level of the test signifies a statistically significant test. As the number of tests increases, the chance of observing some small p-values is very high even when all null hypotheses are true. Consequently, we make wrong conclusions on the hypotheses. This type of potential problem frequently happens when we test several hypotheses simultaneously, i.e., the multiple testing problem. …