# Re: st: Re: multiple imputation and life tables

 From "Margaret Gassanov" To statalist@hsphsun2.harvard.edu Subject Re: st: Re: multiple imputation and life tables Date Sat, 24 Jun 2006 08:52:18 -0400 (EDT)

```Hi Rodrigo,

Thank you for your reply.  I am having trouble understanding the formula
you've provided.  More specifically, I'm not sure what the variable "imp"
is in my dataset.

After running the ice procedure, I have two new variables in my dataset:
_i -- which gives a value of 5 for each case

and

_j

. tab _j

imputation |
number |      Freq.     Percent        Cum.
------------+-----------------------------------
1 |      1,075       20.00       20.00
2 |      1,075       20.00       40.00
3 |      1,075       20.00       60.00
4 |      1,075       20.00       80.00
5 |      1,075       20.00      100.00
------------+-----------------------------------
Total |      5,375      100.00

Are you referring to one of these variables?

Do I manually average each of the values from each of the imputations to
obtain the correct final values?

Also, what are the options "su" and "h"?

Margaret

> Margaret,
>
> Multiple Imputation (MI) allows you to deal with missing values.
> The "solution" is that you will change your missing values for
> several "possibles" values. For example if x has only one missing,
> then MI creates 5 possible values for this missing, that's the
> reason why you have N*5 number of observations.
>
> Then you change your N-1 dataset (assuming only 1 missing
> value) for N*5 dataset. The statistical support is based on
>
> In your case you have to "run" the ltable command conditional
> to the set imputed. If imp is the variable that describes the
> # of imputation type
>
> forvalues i=1/5 {
> ltable...  if imp==`i', su h
> }
>
> Then your statistics (beg total, deaths, lost and rates) should
> be averaged over the 5 tables. You should compute the
> standard errors for these numbers and the formula is in
> Joe Schafer's webpage: http://www.stat.psu.edu/~jls/mifaq.html
> (see the question: How do I combine the results across the
> multiply imputed sets of data?)
>
> I hope this helps you
> Rodrigo.
>
>
>
> ----- Original Message -----
> From: "Margaret Gassanov" <gassanov.1@osu.edu>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Friday, June 23, 2006 4:15 PM
> Subject: st: multiple imputation and life tables
>
>
> Hi,
>
> I'm new at multiple imputation (using the "ice" command), and I would
>
> I've made 5 imputed datasets for an event-history analysis I am doing.  I
> want to use the ltable command to get hazard rates and survival rates, but
> ltable is not supported by micombine.  Thus, my output has the 1075*5 =
> 5375 cases instead of the 1075 cases in the original dataset.
>
> The rates would still be accurate (correct me if I'm wrong), but the
> "beginning total", "deaths", and "lost" numbers are not.  Does anyone have
> suggestions on how to obtain the actual numbers for these three columns of
> data?
>
> Thank you,
> Margaret
> *
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>
>

I try to take one day at a time -- but sometimes several days attack me at
once. -Jennifer Unlimited-

*
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```