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p-value > 1
4 messages · amor Gandhi, Peter Dalgaard, Ista Zahn
amor Gandhi wrote:
Dear all, I am trying to use SAMr-library(samr), it gives me p-value = 1.001, any idea why?
Well, the package maintainer might be a better place to ask. (Bring an example if you do.) However, as a generic matter, the result is obviously nonsensical, and could be due to a sloppy approximation of a distribution function, or maybe it is a (say) Bonferroni-adjusted p-value which is really an upper bound for the correct p-value. Notice, though, that you should only very rarely care about the exact p-value. As soon as it is above 0.1, the message is just that you have not proven that there is an effect.
O__ ---- Peter Dalgaard ?ster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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The maintainer's email address is listed in the package documentation... as I think is the case with all CRAN packages. -Ista
On Fri, Nov 13, 2009 at 11:20 AM, amor Gandhi <amorigandhi at yahoo.de> wrote:
Thank you for your reply. The only contact address of the maintainer is http://www-stat.stanford.edu/~tibs/SAM However, one find no contact when one visit this page. I am not a mathematician, therefore, it is strange for me to get probability bigger that 1, if it is like that should I trust the p-value of 0.004332? Sorry for these questions. Best wishes, Amor --- Peter Dalgaard <p.dalgaard at biostat.ku.dk> schrieb am Fr, 13.11.2009: Von: Peter Dalgaard <p.dalgaard at biostat.ku.dk> Betreff: Re: [R] p-value > 1 An: "amor Gandhi" <amorigandhi at yahoo.de> CC: r-help at stat.math.ethz.ch Datum: Freitag, 13. November 2009, 15:24 amor Gandhi wrote:
Dear all, I am trying to use SAMr-library(samr), it gives me p-value = 1.001, any idea why?
Well, the package maintainer might be a better place to ask. (Bring an example if you do.) However, as a generic matter, the result is obviously nonsensical, and could be due to a sloppy approximation of a distribution function, or maybe it is a (say) Bonferroni-adjusted p-value which is really an upper bound for the correct p-value. Notice, though, that you should only very rarely care about the exact p-value. As soon as it is above 0.1, the message is just that you have not proven that there is an effect. --? ? O__? ---- Peter Dalgaard? ? ? ? ? ????ster Farimagsgade 5, Entr.B ? c/ /'_ --- Dept. of Biostatistics? ???PO Box 2099, 1014 Cph. K ?(*) \(*) -- University of Copenhagen???Denmark? ? ? Ph:? (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)? ? ? ? ? ? ? FAX: (+45) 35327907
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Ista Zahn Graduate student University of Rochester Department of Clinical and Social Psychology http://yourpsyche.org