R help - Jan 2011 - Splitting a Vector

Hi all,

I read in a text book, that you can examine a variable that is colinear 
with others, and giving different ANOVA output and explanatory power 
when ordered differently in the model forula, by modelling that 
explanatory variable, against the others colinear with it. Then, using 
that information to split the vector (explanatory variable) in question, 
into two new vectors, one should correspond to the fitted values and one 
the residuals of the (I think you could call it nested) model. One 
vector therefore should be aligned with the subspacespace defined by the 
other variables colinear with it, and the other will be residual, and so 
orthogonal to the subspace of the colinear variables. Then by including 
these two variables in the origional model - the one that showed the 
order dependency, you can see how much explanatory power the othogonal 
part of the order dependent variable has, at different orders, and in 
principle it shouldn't change, but the vector made from the part 
co-aligned with the co-variates, will change as the order changes - it's 
explanatory power should decreace in ANOVA is it moves away from being 
the first explanatory variable in the model.

Obviously finding the fitted model values and residual required to split 
the vector in two is a simple lm() with the right variables. But how 
would I create two new vectors from this and append them to my 
dataframe? Is there a package or function specially designed with this 
sort of task in mind?

Thanks,
Ben Ward.

I think that you are looking for the 'resid' and 'fitted'
functions, these will give you the residuals and fitted values from an lm object
(that added together gives the original response but are orthogonal to each
other).  Those values can then be assigned to a data frame or used by
themselves.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Ben Ward
> Sent: Thursday, January 06, 2011 6:09 AM
> To: r-help
> Subject: [R] Splitting a Vector
> 
> Hi all,
> 
> I read in a text book, that you can examine a variable that is colinear
> with others, and giving different ANOVA output and explanatory power
> when ordered differently in the model forula, by modelling that
> explanatory variable, against the others colinear with it. Then, using
> that information to split the vector (explanatory variable) in
> question,
> into two new vectors, one should correspond to the fitted values and
> one
> the residuals of the (I think you could call it nested) model. One
> vector therefore should be aligned with the subspacespace defined by
> the
> other variables colinear with it, and the other will be residual, and
> so
> orthogonal to the subspace of the colinear variables. Then by including
> these two variables in the origional model - the one that showed the
> order dependency, you can see how much explanatory power the othogonal
> part of the order dependent variable has, at different orders, and in
> principle it shouldn't change, but the vector made from the part
> co-aligned with the co-variates, will change as the order changes -
> it's
> explanatory power should decreace in ANOVA is it moves away from being
> the first explanatory variable in the model.
> 
> Obviously finding the fitted model values and residual required to
> split
> the vector in two is a simple lm() with the right variables. But how
> would I create two new vectors from this and append them to my
> dataframe? Is there a package or function specially designed with this
> sort of task in mind?
> 
> Thanks,
> Ben Ward.
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.