# [R] Selecting variables in a multivariate regression

Bert Gunter gunter.berton at gene.com
Mon Apr 14 15:33:59 CEST 2014

Well, this is your second post on the same topic, your first having
received no response. So you should suspect something is amiss and
reconsider before continuing, don't you think?

1. I, for one, was not able to make any sense of your query. You do
not appear to understand regression, so I would suggest you spend time
with a local statistical resource before continuing with online
posts.If my understanding of your misunderstanding is correct, you
need to comprehend basics. If not,apologies.

2. Have you read An Introduction to R (ships with R) or an online R
tutorial of your choice? If not, do so before posting here further. We
expect minimal efforts of posters to solve their own problems before
posting. Again, apologies if I err.

Cheers,
Bert

Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374

"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
H. Gilbert Welch

On Sun, Apr 13, 2014 at 8:08 PM, Edson Tirelli <ed.tirelli at gmail.com> wrote:
> I am quite new to R and I am having trouble figuring out how to select
> variables in a multivariate linear regression in R. My google-fu also
> did not find anything.
>
> Pretend I have the following formulas:
>
> P = aX + bY
> Q = cZ + bY
>
> I have a data frame with column P, Q, X, Y, Z and I need to find a, b and c.
>
> If I do a simple multivariate regression:
>
> result <- lm( cbind( P, Q ) ~ X + Y + Z - 1 )
>
> It calculates a coefficient for "c" on P's regression and for "a" on
> Q's regression.
>
> If I calculate the regressions individually then "b" will be different
> in each regression.
>
> How can I select the variables to consider in a multivariate
> regression? I.e., how do I tell R to ignore cZ when calculating P, and
> ignore aX when calculating Q?
>
> Thank you,
> Edson
>
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