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- W1501605627 abstract "ABS TRACT Objective: The problem of testing the equality of two means from normal populations with unknown variances is known as Behrens-Fisher (BF) problem. The difficulty with the BF problem is that exact solutions are not available satisfactorily because nuisance parameters are pres ent. The aim is to compare the different methods for BF problem. Material and Methods: Classical t-test, Welch-Satterthwaite (WS) test, Cochran and Cox (CC) test, Singh-Saxena-Srivastava (SSS) test based on the jackknife procedure and generalized p-value (GP) test are considered. A Monte Carlo simulation study is conducted to evaluate type I error probabilities and powers of these meth ods. Results: Simulation results showed that when variances are unequal, the classical t-test is not an appropriate test because its type I error rate poorly deviates from the nominal level, α=0,05. The WS test has satisfactory type I error rate regardless of sample sizes and unequal variances. Its power appears to be more powerful than the other test when simple sizes are moderate or large. The GP test seems to be very conservative for small sample sizes. The power of the CC test is smallest among the five tests. However, its type I error rate has satisfactory as long as sample sizes are large. When sample sizes are unequal the type I error rate of the SSS test is too conservative or too liberal. Conclusion: The SSS test appears to be less powerful than the GP and WS tests as long as simple sizes are moderate and large. It is concluded that the SSS test is not as good as it has been reported by Singh et al (2002)." @default.
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- W1501605627 date "2014-01-01" @default.
- W1501605627 modified "2023-09-24" @default.
- W1501605627 title "A Simulation Study on Tests for the Behrens-Fisher Problem" @default.
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