[R] significance level (p) for t-value in package zelig

Prof Brian Ripley ripley at stats.ox.ac.uk
Mon Jun 25 11:05:16 CEST 2012


On 25/06/2012 09:32, Rune Haubo wrote:
> According to standard likelihood theory these are actually not
> t-values, but z-values, i.e., they asymptotically follow a standard
> normal distribution under the null hypothesis. This means that you

Whose 'standard'?

It is conventional to call a value of t-like statistic (i.e. a ratio of 
the form value/standard error) a 't-value'.  And that is nothing to do 
with 'likelihood theory' (t statistics predate the term 'likelihood'!).

The separate issue is whether a t statistic is even approximately 
t-distributed (and if so, on what df?), and another is if it is 
asymptotically normal.  For the latter you have to say what you mean by 
'asymptotic': we have lost a lot of the context, but as this does not 
appear to be IID univariate observations:

- 'standard likelihood theory' is unlikely to apply.

- standard asymptotics may well not be a good approximation (in 
regression modelling, people tend to fit more complex models to large 
datasets, which is often why a large dataset was collected).

- even for IID observations the derivation of the t distribution assumes 
normality.

The difference between a t distribution and a normal distribution is 
practically insignificant unless the df is small.   And if the df is 
small, one can rarely rely on the CLT for approximate normality ....

> could use pnorm instead of pt to get the p-values, but an easier
> solution is probably to use the clm-function (for Cumulative Link
> Models) from the ordinal package - here you get the p-values
> automatically.
>
> Cheers,
> Rune
>
> On 23 June 2012 07:02, Bert Gunter <gunter.berton at gene.com> wrote:
>> This advice is almost certainly false!
>>
>> A "t-statistic" can be calculated, but the distribution will not
>> necessarily be student's t nor will the "df" be those of the rse.  See, for
>> example, rlm() in MASS, where values of the t-statistic are given without p
>> values. If Brian Ripley says that p values cannot be straightforwardly
>> calculated by pt(), then believe it!
>>
>> -- Bert
>>
>> On Fri, Jun 22, 2012 at 9:30 PM, Özgür Asar <oasar at metu.edu.tr> wrote:
>>
>>> Michael,
>>>
>>> Try
>>>
>>> ?pt
>>>
>>> Best
>>> Ozgur
>>>
>>> --
>>> View this message in context:
>>> http://r.789695.n4.nabble.com/significance-level-p-for-t-value-in-package-zelig-tp4634252p4634271.html
>>> Sent from the R help mailing list archive at Nabble.com.
>>>
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>>
>>
>>
>> --
>>
>> Bert Gunter
>> Genentech Nonclinical Biostatistics
>>
>> Internal Contact Info:
>> Phone: 467-7374
>> Website:
>> http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
>>
>>         [[alternative HTML version deleted]]
>>
>>
>> ______________________________________________
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>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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>>
>
>
>


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595



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