\begin{Schunk}
\begin{Sinput}
 m0 <- lm(y ~ x1 * x2 + x3f, data = dat) 
 summary(m0)
\end{Sinput}
\begin{Soutput}
Call:
lm(formula = y ~ x1 * x2 + x3f, data = dat)

Residuals:
     Min       1Q   Median       3Q      Max 
-2.50415 -0.53255  0.04636  0.51527  2.30997 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.12175    0.20212  -0.602   0.5489    
x1           0.19990    0.10269   1.947   0.0557 .  
x2          -0.69230    0.10062  -6.880 2.19e-09 ***
x3fmed       0.03265    0.28643   0.114   0.9096    
x3fhi       -0.14434    0.28593  -0.505   0.6153    
x1:x2       -0.50779    0.08849  -5.738 2.34e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.9974 on 69 degrees of freedom
Multiple R-squared:  0.5229,	Adjusted R-squared:  0.4883 
F-statistic: 15.13 on 5 and 69 DF,  p-value: 5.153e-10
\end{Soutput}
\begin{Sinput}
 confint(m0)
\end{Sinput}
\begin{Soutput}
                   2.5 %     97.5 %
(Intercept) -0.524962270  0.2814709
x1          -0.004972956  0.4047652
x2          -0.893032200 -0.4915659
x3fmed      -0.538768748  0.6040747
x3fhi       -0.714759429  0.4260814
x1:x2       -0.684335100 -0.3312497
\end{Soutput}
\end{Schunk}
