A problem of multiple significance tests

Significance levels for multiple tests

Let X 1 . . . . . X, be n random variables, with cumulative distribution functions F1, . . . , F,. Define ¢i := Fi(Xi) for all i, and let ~(1) ~< ... ~< ~(,) be the order statistics of the (~)~. Let cq ~< ... ~< ~. be n numbers in the interval [0, 1]. We show that the probability of the event R := {(") ~< ct~ for all 1 ~< i ~< n} is at most min~n~Ji }. Moreover, this bound is exact: for any giv...

Sensitivity of Tests of Significance: A Problem Posed

THIS paper contains a preliminary examination o f the effect o f using the dichotomy (o, i ) instead o f actual measurement in the study o f relation­ ship. First, the simplest case possible is dealt w i t h , i n the hope o f inspiring, or provoking, more thorough treatment by others. O f course, dichotomy or other ordinal treatment has to be used when measure­ ment is inconceivable, e.g. when...

Multiple significance tests: the Bonferroni method.

Some Remarks on Simes Type Multiple Tests of Significance

Simes' theorem, posed in a multiple testing setup, has its genesis in the classical ballot theorem in uniform order statistics. The purpose of this note is to comment on this rediscovery of the Ballot theorem in multiple testing theory, and with a view to enhance scope of applications, to stress its ramifications in the same context. This privides sharper error rates. AMS Subject Classification...

the washback effect of discretepoint vs. integrative tests on the retention of content in knowledge tests

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