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@article{Young:2016:biomet/asw021,
author = {Young, GA and Lee, SMS},
doi = {biomet/asw021},
journal = {Biometrika},
pages = {641--652},
title = {Distribution of likelihood-based p-values under a local alternative hypothesis},
url = {http://dx.doi.org/10.1093/biomet/asw021},
volume = {103},
year = {2016}
}

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TY  - JOUR
AB  - We consider inference on a scalar parameter of interest in the presence of a nuisance parameter, using a likelihood-based statistic which is asymptotically normally distributed under the null hypothesis. Higher-order expansions are used to compare the repeated sampling distribution, under a general contiguous alternative hypothesis, of pp-values calculated from the asymptotic normal approximation to the null sampling distribution of the statistic with the distribution of pp-values calculated by bootstrap approximations. The results of comparisons in terms of power of different testing procedures under an alternative hypothesis are closely related to differences under the null hypothesis, specifically the extent to which testing procedures are conservative or liberal under the null. Empirical examples are given which demonstrate that higher-order asymptotic effects may be seen clearly in small-sample contexts.
AU  - Young,GA
AU  - Lee,SMS
DO  - biomet/asw021
EP  - 652
PY  - 2016///
SN  - 1464-3510
SP  - 641
TI  - Distribution of likelihood-based p-values under a local alternative hypothesis
T2  - Biometrika
UR  - http://dx.doi.org/10.1093/biomet/asw021
UR  - http://hdl.handle.net/10044/1/38738
VL  - 103
ER  -

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Professor Alastair Young

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