Sequential Monte Carlo p-values

doi:10.1093/biomet/78.2.301

Biometrika 1991 78(2):301-304; doi:10.1093/biomet/78.2.301
© 1991 by Biometrika Trust

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Sequential Monte Carlo p-values

JULIAN BESAG¹ and PETER CLIFFORD²

¹Department of Mathematics and Statistics, University of Newcastle upon Tyne Newcastle upon Tyne NE1 7RU, U.K.
²Department of Statistics, University of Oxford 1 South Parks Road, Oxford OX1 3TG, U. K.

The assessment of statistical significance by Monte Carlo simulationmay be costly in computer time. This paper looks at a numberof ways of calculating exact Monte Carlo p-values by sequentialsampling. Such p-values are shown to have properties similarto those obtained by sampling with a fixed sample size. Bothstandard and generalized Monte Carlo procedures are discussedand, in particular, a sequential method is proposed for dealingwith situations in which values can only be conveniently generatedusing a Markov chain, conditioned to pass through the observeddata.

Key Words: Monte Carlo testing • Markov chain • p-value • Sequential estimation • Sequential test • Significance test

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				J. A. Goble, Y. Zhang, Y. Shimansky, S. Sharma, and N. V. Dounskaia Directional Biases Reveal Utilization of Arm's Biomechanical Properties for Optimization of Motor Behavior J Neurophysiol, September 1, 2007; 98(3): 1240 - 1252. [Abstract] [Full Text] [PDF]

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