imputation of cohort data in long format without converting to wide format

[DavidsM]

Hello community,

I have a very large data set with many years of repeatedly measured data an over 180 variables per observations. I want to impute missing data for the first two years but converting these variables to wide format to capture record for every time of measurement and then impute is extremely tasking and the imputations are computationally demanding.

Is there any way to directly impute longitudinal data in long format using sas? 

I will be glad to be advised and assisted and I wish to use FCS method in the imputaion.

Thank in advance

[ChrisNZ]

Are the missing variables  continuous ? 

An example of the before/after data would be nice too.

[DavidsM]

The are both continuous an categorical variables. The data is arranged with person 

Data structure before

ID    YEAR    WEIGHT    HEIGHT     SMOKING    EXERCISE

01    2000           .              175                   .                  1

01    2001           57           175                  1                  1

01    2002           .              175                   .                  1

01    2003           57           175                  1                  1

01    2004           .              175                   .                  1

02    2000           57             .                     1                  1

02    2001           .              168                  .                  1

02    2004          57            169                  1                  1

Data structure after(Only one observation per person with missing values for year 2000 values imputed .

ID    YEAR    WEIGHT2000   HEIGHT2000   SMOKING2000    EXERCISE2000

01    2000            57               175                           1                          1

02    2000            57                168                          1                          1

I want to have the values for the first year imputed so that I use the information for the first year in my analysis. There many observations per person and the number of observations is not similar but I want to have one summary of imputed data for each person(One entry per person).

Thank you for assistance. 

[ScottBass]

I can help with your issue, but first edit your original post with a self-contained data step using datalines, posted using "Insert SAS code", that I can cut-and-paste into SAS and run without error.

[DavidsM]

DATA HAVE;
INPUT       ID     YEAR      WEIGHT     HEIGHT     SMOKING    EXERCISE
DATELINES;

            01      2000        .          175          .        1

            01      2001        57         175          1        1

            01      2002        .          175          .        1

            01      2003        57         175          1        1

            01      2004        .          175          .        1

            02      2000        57         .            1        1

            02      2001        .          168          .        1

            02      2004        57         169          1        1
   
 



DATA HAVE;
INPUT      ID    YEAR  WEIGHT  HEIGHT SMOKING EXERCISE
DATELINES;

           01    2000    57    175      1     1

           02    2000    57    168      1     1

[ChrisNZ]

This program is not even close to being error free.

So you want a perfectly working program that answers your question but can't be bothered supplying a working sample program?

Also why only one year in the output? Do you take the minimum non-missing value of all variables? Is this how you want to impute?

[ScottBass]

---

@ChrisNZ wrote:

This program is not even close to being error free.

So you want a perfectly working program that answers your question but can't be bothered supplying a working sample program?

Also why only one year in the output? Do you take the minimum non-missing value of all variables? Is this how you want to impute?

---

Yep, I completely agree with Chris.  I know how to code this issue - it may not be perfect but would work - but refuse to expend more effort in answering your question than you (twice) expended in posting it. 

Once you learn what cut-and-paste working code into SAS means, perhaps you'll get a working reply.

Here are some hints:

• Transpose
• Filter non-missing values
• Select minimum year with non-missing values
• Transpose again
• Set that year to a dummy value, say year 0
• Interleave with your existing data
• Use update statement to do LOCF.
• Transpose again to name your data as FOO2000, FOO2001, etc

See, wouldn't this have been so much easier if you'd provided working code that we could run with.

Hit Google or search these forums for working examples of all the above.  I'm sure you'll work it out eventually.

Good luck, I'm unsubscribing from this one...