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It is common in econometric applications that several hypothesis tests are carried out at the same time. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. In this paper, we suggest a stepwise multiple testing procedure which asymptotically...
Persistent link: https://www.econbiz.de/10010547259
It is common in econometric applications that several hypothesis tests are carried out at the same time. The problem then becomes how to decide which hypotheses to reject, accounting for the multitude of tests. In this paper, we suggest a stepwise multiple testing procedure which asymptotically...
Persistent link: https://www.econbiz.de/10005771987
Consider the problem of testing k hypotheses simultaneously. In this paper, we discuss finite and large sample theory of stepdown methods that provide control of the familywise error rate (FWE). In order to improve upon the Bonferroni method or Holm's (1979) stepdown method, Westfall and Young...
Persistent link: https://www.econbiz.de/10005772539
Consider the problem of testing s hypotheses simultaneously. In this paper, we derive methods which control the generalized familywise error rate given by the probability of k or more false rejections, abbreviated k-FWER. We derive both single-step and stepdown procedures that control the k-FWER...
Persistent link: https://www.econbiz.de/10005627785
this property via a simulation study and two empirical applications. In particular, the bootstrap method is competitive …
Persistent link: https://www.econbiz.de/10005627803
Consider the problem of testing s hypotheses simultaneously. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the probability of even one false rejection, the familiar familywise error rate (FWER). In many applications, particularly...
Persistent link: https://www.econbiz.de/10005463520
There has been a recent interest in reporting p-values adjusted for resampling-based stepdown multiple testing procedures proposed in Romano and Wolf (2005a,b). The original papers only describe how to carry out multiple testing at a fixed significance level. Computing adjusted p-values instead...
Persistent link: https://www.econbiz.de/10011663178
This paper reviews important concepts and methods that are useful for hypothesis testing.First, we discuss the Neyman-Pearson framework. Various approaches to optimalityare presented, including finite-sample and large-sample optimality. Then, some of the mostimportant methods are summarized, as...
Persistent link: https://www.econbiz.de/10005868540
Consider the problem of testing s hypotheses simultaneously. In order to deal with themultiplicity problem, the classical approach is to restrict attention to procedures that controlthe familywise error rate (FWE). Typically, it is known how to construct tests of the individualhypotheses, and...
Persistent link: https://www.econbiz.de/10005868541
There has been a recent interest in reporting p-values adjusted for resampling-based stepdown multiple testing procedures proposed in Romano and Wolf (2005a,b). The original papers only describe how to carry out multiple testing at a fixed significance level. Computing adjusted p-values instead...
Persistent link: https://www.econbiz.de/10011432996