[R] How do we get two-tailed p-values for rlm?
Prof Brian Ripley
ripley at stats.ox.ac.uk
Sat Jan 19 07:56:38 CET 2008
On Fri, 18 Jan 2008, Darren Weber wrote:
> How do we get 2-tailed p-values for the rlm summary?
>
> I'm using the following:
>
>> fit <- rlm(oatRT ~ oatoacData$erp, psi=psi.bisquare, maxit=100,
> na.action='na.omit')
>> fitsum <- summary(fit, cor=F)
>> print(fitsum)
>
> Call: rlm(formula = oatRT ~ oatoacData$erp, psi = psi.bisquare, maxit = 100,
>
> na.action = "na.omit")
> Residuals:
> Min 1Q Median 3Q Max
> -120.616 -50.637 -5.895 60.356 199.066
>
> Coefficients:
> Value Std. Error t value
> (Intercept) 574.5204 25.8582 22.2181
> oatoacData$erp 11.5963 5.3525 2.1665
>
> Residual standard error: 83.29 on 36 degrees of freedom
> (2 observations deleted due to missingness)
>> i <- length(fitsum$coefficients) - dim(fitsum$coefficients)[1] + 1
>> j <- length(fitsum$coefficients)
>> tvalues <- fitsum$coefficients[i:j]
>> pvalues <- pt(tvalues, df=fitsum$df[2])
>> print(rbind(tvalues, pvalues))
> [,1] [,2]
> tvalues 22.21815 2.1664977
> pvalues 1.00000 0.9815145
>
>
> If I use the lower.tail=FALSE argument to pt, then I seem to get only the
> p-values for anything > my t value. Do have to call pt twice, once with
> lower.tail=TRUE and once with lower.tail=FALSE to get 2-tailed p-values?
The t distribution is symmetric, so you just double the upper tail value.
(See the code of summary.lm for how it does this.)
BUT, what justifies the assumption of a t distribution here?
Even for lm, the calculations rely on a normal distribution of errors, and
robust methods are used precisely to avoid that.
rlm() is support software for a book, and this issue and alternatives
(e.g. bootstrapping) are discussed there.
>
> Thanks in advance, Darren
>
> [[alternative HTML version deleted]]
>
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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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