Masking Effect on Tests for Outliers in Exponential Models
Abstract The masking effect in cases of tests for outlier(s) is defined and quantified by the loss in power due to the presence of more than the anticipated number of discordant observations in the sample. This effect is illustrated in cases of some commonly used outlier tests for exponential samples—namely, Dixon-type tests and the Cochran test. A comparison between the performances of the modified Dixon-type test and the Cochran test is made. Tables for powers of these tests are presented for different sample sizes and different values of discordancy parameter. An illustrative example is presented to support the conclusion that Cochran and modified Dixon-type tests do not suffer from the masking effect in the presence of two outliers.