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Re: st: robust standard errors, sureg, & suest
okay. the unit of analysis of the dataset is a health insurance
company and I am imputing rates. For example, the percent of a health
plan's diabetic members that recieved a specific treatment. I was
actually thinking of running my own simulation study to assess the
statistical properties of the estimation technique I am using, but I
think I'll need a statistician to advise me.
Woolton
On Thu, Aug 27, 2009 at 10:13 AM, Austin Nichols<[email protected]> wrote:
> Woolton Lee<[email protected]> :
> I am just guessing that modeling covariances in the data well at the
> imputation step will be crucial, and that you will need a lot more
> imputations than usual, perhaps 100 instead of 5 or 10. Just
> guessing, as I say. You should run your own simulation--what is your
> data structure? What are you imputing?
>
> On Thu, Aug 27, 2009 at 10:02 AM, Woolton Lee<[email protected]> wrote:
>> I am planning to estimate a multi equation model using multiply
>> imputed data (5 imputations). I plan to use sureg and mim then use
>> suest to recover robust standard errors for the parameter estimates.
>> I am assuming this will work from what I've read in the help file but
>> I am not certain if there are problems to implementing this plan that
>> I haven't anticipated. Could someone please confirm that as far as
>> implementing my idea, it will work? Thanks.
>>
>> I believe one problem with what I've planned is that combining
>> multiply imputed estimates using sureg may not be guaranteed to yield
>> statistically valid results - there may not have been any simulation
>> studies to verify that this approach to estimation will be unbiased
>> and consistent, etc. If there is anyone that can comment on this as
>> well please do.
>>
>
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