Higher significance with smaller samples: A modified Sequential Probability Ratio Test
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We describe a modified sequential probability ratio test that can be used to reduce the average sample size required to perform statistical hypothesis tests at specified levels of significance and power. Examples are provided for Z-tests, T-Tests, and tests of binomial success probabilities. A description of a software package to implement the tests is provided. We also compare the sample sizes required in fixed design tests conducted at 5 to the average sample sizes required in sequential tests conducted at 0.5 significance levels, and find that the two sample sizes are approximately the same. This illustrates that the proposed sequential tests can provide higher levels of significance using smaller sample sizes.
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