On 11/9/2005 3:48 PM, Oliver Lyttelton wrote:>
>
> Hi,
>
> Sorry for this one as its pretty basic but I've taken a look for info
and
> couldn't find any...
>
> My question is, does the order of main effect terms in a model
specification
> have any impact on the model R fits or not. (in particular when using lm).
> ie
>
> Can A~X+Y+Z lead to different results to A~Z+Y+X, and if so in what
> circumstances, and how much should I worry about it?
>
> I believe this is an implementation detail as it depends on the way the
> fitting algorithm works, but it would be great to have a few lines to plug
> this gap in my knowledge...
Definitely yes, in the case of collinear terms. For example,
> X <- rnorm(10)
> Y <- rnorm(10)
> Z <- X
> A <- rnorm(10)
> lm(A ~ X+Y+Z)
Call:
lm(formula = A ~ X + Y + Z)
Coefficients:
(Intercept) X Y Z
-0.3474 -0.1166 -0.2203 NA
> lm(A ~ Z+Y+X)
Call:
lm(formula = A ~ Z + Y + X)
Coefficients:
(Intercept) Z Y X
-0.3474 -0.1166 -0.2203 NA
In one case X gets a coefficient and Z doesn't, but the other is the
opposite.
I suspect there would be differences due to rounding in other
situations, and they might be noticeable in the case of near-collinearity.
Duncan Murdoch