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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