We study the actual significance level which results from performing repeated likelihood ratio tests over time. We present a general method for estimating the actual significance level when sampling from an exponential family, and apply it to problems of testing hypotheses about means, variance, correlations and failure rates. Our results confirm and extend those of earlier authors that the actual significance level may exceed the nominal one by several times.
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Michael Woodroofe (1979) studied this question.
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