Including indicator variables allows for differences in the average level
of your dependent variable across groups, while clustering only allows
differences in the variance/standard errors.
Also, including indicator variables doesn't inherently imply that
observations are independent across groups (or correlated within a group).
Dave
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On Mon, 8 Nov 2004 [email protected] wrote:
> Hello All,
>
> I understand that clustering specifies that observations be independent
> across groups while allowing for changes in variance within a group. My
> question is how is this different than controlling for a group with an
> indicator (0/1) variables.
>
> For example, If my data contains patient data for 12 hospitals and my LHS
> variable is (0/1) for recovery and my RHS variables include characteristic
> variables, treatment type, etc. What is the difference between clustering
> on hospital or creating an indicator variable for each hospital?
>
> Thanks in advance for any commentary,
>
> David J. Bernstein, Ph.D.
> [email protected]
>
>
>
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