[R] How to run mixed model with related independent variables
bgunter.4567 at gmail.com
Fri Jan 26 18:53:04 CET 2018
R-help is for help on R programming and related functionality, not
statistics, though the intersection is sometimes nonempty.
However, you appear to be seeking what might be described as a statistics
tutorial. You might try a statistics list like stats.stackexchange.com or
just do some studying on your own. I believe you need to learn about
"generalized linear models" which is implemented in the glm() function in
the stats package (as well as others, probably). However, you will need to
gain some background to use it properly, and this is not the venue for that.
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Fri, Jan 26, 2018 at 9:09 AM, Sariya, Sanjeev <ss5505 at cumc.columbia.edu>
> I've data that look like:
> Outcome V1_AA V1_EU V1_NA V2_AA V2_EU V2_NA
> 0 0.046 1.001 0.954 0.045 1.001 0.954
> 0 0.007 1 0.993 0.007 1
> 1 1.774 0.217 0.009 1.774 0.217 0.009
> 1 0.004 1.996 0 0.004 1.996 0
> 1 1.001 0.997 0.002 1.001 0.997 0.002
> 0 0.94 0.998 0.061 0.94 0.998 0.061
> 0 0.587 1.407 0.006 0.587 1.408 0.006
> 1 0.019 1.978 0.003 0.018 1.979 0.003
> Column Outcome is dependent variable. It's dichotomous either 0 or 1.
> Column 1st, 2nd, 3rd are three components of V1, similarly next three for
> V2. Sum of V1_AA, V1_EU and V1_NA will be two at each row. Similarly for V2
> variable's components.
> Here the three predictors (I'm referring as component) are related. If AA
> is higher then, NA and EU will be lesser.
> I cannot simply use multivariate regression as:
> Y ~ V1_AA + V1_EU + V1_NA
> How do I proceed with these data?
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