Relative importance of covariates is in
general highly elusive. Someone who
worked in your institution until his
recent death -- Fred Mosteller -- warned
that covariates come as a bunch, not
as a set of individual variables, in his
book with John Tukey, "Data analysis and
regression" (1977). And that's just one
of several accounts repeating the same basic
idea.
I know that doesn't answer your question,
except insofar as you asked for "any advice".
Nick
[email protected]
Hillel Alpert
> Can someone please advise:
>
> How can we determine the proportion of variance explained per
> covariate in a model that is
> based on maximum likelihood estimation?
>
> The model in hand is generated with xtmixed, and I wish to
> determine how much of the model is explained by one of the
> independent variables. The beta coefficient for the model
> with only that
> variable is 0.02. The beta coefficient for this variable
> when the model others variables is about
> 0.01. Would the difference between these coefficients be indicative?
>
> Any advice is much appreciated.
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