Distribution Theory for Group Sequential Analysis of General Linear Models
نویسندگان
چکیده
SUMMARY We derive the joint distribution of the sequence of estimates of the parameter vector in a normal general linear model when data accumulate over a series of analyses. This sequence of estimates has a remarkably simple covariance structure, even when observations are correlated, allowing standard group sequential tests to be applied in very general settings. If observations' variances and covariances depend on an unknown scale factor 2 , the joint distribution of the sequence of estimates of and 2 has a simple form, again even in the case of correlated observations. From these results, we establish a general treatment of group sequential t, 2 and F-tests.
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تاریخ انتشار 2007