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?
Thanks in advance, Darren
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