\begin{Schunk}
\begin{Sinput}
 dat <- genCorrelatedData(1000, stde=5)
 dat$x3 <- rnorm(1000)
 dat$x4 <- rnorm(1000)
 dat$x5 <- factor(c( rep("A", 700), rep("B", 300)))
 m2 <- lm( y ~ x1 + x2 + x3 + x4 + x5, data=dat)
 m2.data <- model.data(m2)
 newdata1 <- newdata(m2, predVals = list(x1 = "quantile"))
 newdata1$fit <- predict(m2, newdata=newdata1)
 print(newdata1, digits = 3)
\end{Sinput}
\begin{Soutput}
    x1   x2     x3       x4 x5  fit
1 43.3 50.5 0.0162 -0.00544  A 18.6
2 50.2 50.5 0.0162 -0.00544  A 20.0
3 57.2 50.5 0.0162 -0.00544  A 21.4
\end{Soutput}
\end{Schunk}
