Programming the statistical procedures from SAS

Variable selection in Proc Logistic - dealing with missing values

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Frequent Contributor
Posts: 76

Variable selection in Proc Logistic - dealing with missing values

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Dear All,

 

Here I have a question about variale selection. Say I have the following data set:

 

Age    Sex    weight     Pass

15          0           70           1

17          1              -           0

16           -           60           1   ;

 

And I want to use logistic regression to predice pass using age, sex and weight . also I want to use backwards variable selection to selsect significant covariate. So I coded as following:

 

proc logistic data=have descending;

model pass= age sex weight /selection=backward fast;

run;

 

However, since I have missing data here. The program only use the entry that has complete observation based on full model, therefore the first enrty.

 

But I want it to enclude more observation as eleminate covariates, that is when model only with age and sex, i want it to use first two entries. Is there a way to realize this in SAS?

 

Thank you very much!!!

 

Best,

 

 

 

HereH

Super User
Posts: 11,810

Re: Variable selection in Proc Logistic - dealing with missing values

Posted in reply to Xiaoningdemao

The procedure will only use records that have values for all the model variables.

 

You might try imputation to replace missing values. There are a number of ways but if you have significant percentage of missing values for a given variable then your resulting model is going to be suspect.

 

What percentage of your records are missing one or more of the variables?

Respected Advisor
Posts: 5,053

Re: Variable selection in Proc Logistic - dealing with missing values

Posted in reply to Xiaoningdemao

You could screen your predictors with PROC HPSPLIT. It offers three methods for dealing with missing predictors. The output decision tree is a crude model but will show you which variables are the most important predictors.

PG
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