That's good insight, and gives me some good ideas for what direction
to this. Thanks everyone !
Doug
P.S. - I guess if you have a significant interaction, that implies the
slopes of the individual regression lines are significantly different
anyway, doesn't it...
On Tue, Sep 14, 2010 at
Hi Thomas,
Thanks for the additional information.
Just wondering, and hoping to learn ... would any lack of homogeneity of
variance (which is what I believe you mean by different stddev estimates) be
found when performing standard regression diagnostics, such as residual
plots, Levene's test (or
If you are interested in exploring the homogeneity of variance assumption,
I would suggest you model the variance explicitly. Doing so allows you to
compare the homogeneous variance model to the heterogeneous variance model
within a nested model framework. In that framework, you'll have
Hello,
We've got a dataset with several variables, one of which we're using
to split the data into 3 smaller subsets. (as the variable takes 1 of
3 possible values).
There are several more variables too, many of which we're using to fit
regression models using lm. So I have 3 models fitted
Hello Doug,
Perhaps it would just be easier to keep your data together and have a
single regression with a term for the grouping variable (a factor with
3 levels). If the groups give identical results the coefficients for
the two non-reference grouping variable levels will include 0 in their
If you'll allow me to throw in two cents ...
Like Michael said, the dummy variable route is the way to go, but I believe
that the coefficients on the dummy variables test for equal intercepts. For
equality of slopes, do we need the interaction between the dummy variable
and the explanatory
Thanks for turning my half-baked suggestion into something that would
actually work Cliff :)
Michael
On 14 September 2010 12:27, Clifford Long gnolff...@gmail.com wrote:
If you'll allow me to throw in two cents ...
Like Michael said, the dummy variable route is the way to go, but I believe
Allow me to add to Michael's and Clifford's responses.
If you fit the same regression model for each group, then you are also
fitting a standard deviation parameter for each model. The solution
proposed by Michael and Clifford is a good one, but the solution assumes
that the standard deviation
8 matches
Mail list logo
