On Combining Independent Tests In Case Of Conditional Normal Distribution

In statistics we often experience combining n-independent tests of simple hypothesis, versus a one-tailed alternative as n approaches infinity. In the present study, we consider combining independent tests in case of conditional normal distribution with probability density function when have a distribution function (DF) Four nonparametric combination procedures (Fisher, logistic, sum of p-values and inverse normal) were compared via the exact Bahadur slope. We concluded that the inverse normal procedure is better than the other procedures.