Hello Fernando
First, ask yourself what Gosta Ekman would have said if you asked him
this question. He would have asked "does it make any difference to
your conclusion?" He might also have asked you "Did you do a visual
test?" Plot your data as a QQ plot or density plot?
If the test doesn't make a difference in conclusions, it is a waste of
your time (and ours) to worry about how to cite a
'combined p.value' (if such an animal exists), presumably to
more decimal places than is worth worrying about.
If the test *does* make a difference about normality, then ask yourself
does the degree of non-normality impede my substantive conclusions.
HTH,
-ichael
On 7/10/16 3:39 AM, Fernando Marmolejo Ramos wrote:
hi marc
say i have a vector with some x number of observations
x = c(23, 56, 123, ..... )
and i want to know how normal it is
as there are many normality tests, i want to combine their p.values
so, suppose i use shapiro.wilk, anderson darling and jarque bera and each will
give a pvalue
i could simply average those p,values but to my knowledge that approach is
biased
so i thought, in the same way there is a method to combine independent pvalues
(e.g. stouffer method); is there a way to combine dependent pvalues?
best
f
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Fernando Marmolejo-Ramos
Postdoctoral Fellow
Gösta Ekman Laboratory
Department of Psychology
Stockholm University
Frescati Hagväg 9A, Stockholm 114 19
Sweden
ph = +46 08-16 46 07
website = http://sites.google.com/site/fernandomarmolejoramos/
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
________________________________________
From: Marc Girondot <marc.giron...@u-psud.fr>
Sent: Sunday, 10 July 2016 8:25 AM
To: r-help@r-project.org; Fernando Marmolejo Ramos
Subject: Re: [R] dependent p.values
Le 09/07/2016 à 17:17, Fernando Marmolejo Ramos a écrit :
hi all
does any one know a method to combine dependent p.values?
First, it is a stats question and not a R question. So you could have
better chance to ask this in stackexchange forum.
Second, your question is difficult to answer without context: why
p.values are dependent ? Do they come from the same dataset ? Or are
they linked by an external source ? For both these situations, combining
dependent p.values seems strange for me.
When you will ask question in stackexchange, be more precise.
Sincerely,
Marc Girondot
--
__________________________________________________________
Marc Girondot, Pr
Laboratoire Ecologie, Systématique et Evolution
Equipe de Conservation des Populations et des Communautés
CNRS, AgroParisTech et Université Paris-Sud 11 , UMR 8079
Bâtiment 362
91405 Orsay Cedex, France
Tel: 33 1 (0)1.69.15.72.30 Fax: 33 1 (0)1.69.15.73.53
e-mail: marc.giron...@u-psud.fr
Web: http://www.ese.u-psud.fr/epc/conservation/Marc.html
Skype: girondot
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