Hello dear all,

I am unable to understand why when I run the following three lines:

set.seed(4254)
> a <- data.frame(y = rnorm(40), x=ordered(sample(1:5, 40, T)))
> summary(lm(y ~ x, a))


The output I get includes factor levels which are not relevant to what I am
actually using:

Call:
> lm(formula = y ~ x, data = a)
> Residuals:
>     Min      1Q  Median      3Q     Max
> -1.4096 -0.6400 -0.1244  0.5886  2.1891
> Coefficients:
>             Estimate Std. Error t value Pr(>|t|)
> (Intercept) -0.03276    0.15169  -0.216    0.830
> x.L         -0.28968    0.33866  -0.855    0.398
> x.Q         -0.38813    0.33851  -1.147    0.259
> x.C         -0.27183    0.34027  -0.799    0.430
> x^4          0.25993    0.33935   0.766    0.449
> Residual standard error: 0.9564 on 35 degrees of freedom
> Multiple R-squared: 0.08571, Adjusted R-squared: -0.01878
> F-statistic: 0.8202 on 4 and 35 DF,  p-value: 0.5211


I am guessing that this is having something to do with the contrast matrix
that is used, but this is not clear to me.
Can anyone suggest a good read, or an explanation?

Thanks.


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