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Re: st: Missing data in dataset, long format


From   Alfonso Sanchez-Penalver <[email protected]>
To   "[email protected]" <[email protected]>
Subject   Re: st: Missing data in dataset, long format
Date   Thu, 21 Nov 2013 14:04:30 -0500

As a first approach if the variable with missing observations can be explained by other variables you have you can always do a regression, predict the expected values and replace the missing ones with the predictions. This has many drawbacks but you mentioned something crude, and at least captures some variation versus an unconstrained mean.

Alfonso Sanchez-Penalver

> On Nov 21, 2013, at 1:48 PM, Christina Wei <[email protected]> wrote:
> 
> I have a rather odd question for the group, but currently I am dealing
> with a dataset that has only a few missing data.  Without going into
> the details of exploring patterns of "missingness," is there a simple
> method for filling in missing data without engaging in any fancy
> methods like multiple imputation?  My goal is to crudely study my
> database right now before I embark on intense statistical analysis.
> 
> Also, my data is in long format, if that makes any difference.
> 
> Thanks,
> Christina
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