[R] Question about mixed-effects models example (Pinheiro and Bates)

[Shravan Vasishth]

Hi all,

I'm trying to figure out the example about mixed models in the Pinheiro
and Bates book (Mixed-Effects Models in S and S-Plus, 2000, pp. 135-137).
One thing I don't understand is:

When I run the command

     fm1Orth.lm <- lm( distance ~ age, Orthodont )

followed by

    fm2Orth.lm <- update( fm1Orth.lm, formula = distance ~ Sex*age )

and then do

    summary(fm2Orth.lm)

in the output, there's "SexFemale" instead of "Sex" (see below). Why?

Call:
lm(formula = distance ~ Sex + age + Sex:age, data = Orthodont)

Residuals:
    Min      1Q  Median      3Q     Max
-5.6156 -1.3219 -0.1682  1.3299  5.2469

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)    16.3406     1.4162  11.538  < 2e-16 ***
SexFemale       1.0321     2.2188   0.465    0.643
age             0.7844     0.1262   6.217 1.07e-08 ***
SexFemale:age  -0.3048     0.1977  -1.542    0.126
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Residual standard error: 2.257 on 104 degrees of freedom
Multiple R-Squared: 0.4227,     Adjusted R-squared: 0.4061
F-statistic: 25.39 on 3 and 104 DF,  p-value: 2.108e-12

The entire session was as below:

> library(nlme)
Loading required package: nls
> data(Orthodont)
> fm1Orth.lm <- lm( distance ~ age, Orthodont )
> summary(fm1Orth.lm)

Call:
lm(formula = distance ~ age, data = Orthodont)

Residuals:
    Min      1Q  Median      3Q     Max
-6.5037 -1.5778 -0.1833  1.3519  6.3167

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  16.7611     1.2256  13.676  < 2e-16 ***
age           0.6602     0.1092   6.047 2.25e-08 ***
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Residual standard error: 2.537 on 106 degrees of freedom
Multiple R-Squared: 0.2565,     Adjusted R-squared: 0.2495
F-statistic: 36.56 on 1 and 106 DF,  p-value: 2.248e-08

> fm2Orth.lm <- update( fm1Orth.lm, formula = distance ~ Sex*age )
> summary(fm2Orth.lm)

Call:
lm(formula = distance ~ Sex + age + Sex:age, data = Orthodont)

Residuals:
    Min      1Q  Median      3Q     Max
-5.6156 -1.3219 -0.1682  1.3299  5.2469

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)    16.3406     1.4162  11.538  < 2e-16 ***
SexFemale       1.0321     2.2188   0.465    0.643
age             0.7844     0.1262   6.217 1.07e-08 ***
SexFemale:age  -0.3048     0.1977  -1.542    0.126
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Residual standard error: 2.257 on 104 degrees of freedom
Multiple R-Squared: 0.4227,     Adjusted R-squared: 0.4061
F-statistic: 25.39 on 3 and 104 DF,  p-value: 2.108e-12


Thanks in advance,

-- 
Shravan Vasishth
http://www.ling.ohio-state.edu/~vasishth

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