[R] poly() in lm() leads to wrong coefficients (but correct residuals)
Markus Jäntti
markus.jantti at iki.fi
Wed Jun 29 18:43:56 CEST 2005
On Wed, 2005-06-29 at 18:19 +0200, Andreas Neumann wrote:
> Dear all,
>
> I am using poly() in lm() in the following form.
>
> 1> DelsDPWOS.lm3 <- lm(DelsPDWOS[,1] ~ poly(DelsPDWOS[,4],3))
>
> 2> DelsDPWOS.I.lm3 <- lm(DelsPDWOS[,1] ~ poly(I(DelsPDWOS[,4]),3))
>
> 3> DelsDPWOS.2.lm3 <-
> lm(DelsPDWOS[,1]~DelsPDWOS[,4]+I(DelsPDWOS[,4]^2)+I(DelsPDWOS[,4]^3))
>
> 1 and 2 lead to identical but wrong results. 3 is correct. Surprisingly
> (to me) the residuals are the same (correct) in all cases although the
> coefficients of 1 (and 2) are wrong and do not in any way match the
> stated regression polynomial. (summaries below)
>
> QUESTION:
> Is there a correct way to use poly() in lm() since version 3 becomes quite
> tedious if used more often especially with higher order polynomials?
>
The coefficients using 1 and 2 are not incorrect.
poly() defines orthogonal polynomials, whereas your
DelsPDWOS[,4]+I(DelsPDWOS[,4]^2)+I(DelsPDWOS[,4]^3
contruct defines an ordinary polynomial.
You should be able to recover version 3 coefficients from 1 and 2.
See help(poly)
> x <- runif(10)
> x
[1] 0.1878 0.2415 0.5834 0.6556 0.4112 0.3399 0.8144 0.1134 0.7360
0.0463
> model.matrix(~ poly(x, 2))
(Intercept) poly(x, 2)1 poly(x, 2)2
1 1 -0.27648 -0.0452
2 1 -0.21052 -0.1899
3 1 0.20937 -0.2708
4 1 0.29799 -0.1021
5 1 -0.00212 -0.4117
6 1 -0.08970 -0.3621
7 1 0.49297 0.4968
8 1 -0.36790 0.2148
9 1 0.39672 0.1620
10 1 -0.45033 0.5082
attr(,"assign")
[1] 0 1 1
> model.matrix(~ x + I(x^2))
(Intercept) x I(x^2)
1 1 0.1878 0.03528
2 1 0.2415 0.05834
3 1 0.5834 0.34040
4 1 0.6556 0.42982
5 1 0.4112 0.16911
6 1 0.3399 0.11554
7 1 0.8144 0.66320
8 1 0.1134 0.01286
9 1 0.7360 0.54169
10 1 0.0463 0.00214
attr(,"assign")
[1] 0 1 2
>
Regards,
--
Markus Jantti
Abo Akademi University
markus.jantti at iki.fi
http://www.iki.fi/~mjantti
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