BookmarkSubscribeRSS Feed
npandis
Fluorite | Level 6

Hi,

I have a dataset with approximately 1300 observations and I am interested in fitting a series of models using: 

proc logistic

proc surveylogistic

proc genmod

Some of the included covariates have missing values and the missing values of the covariates belong to different observations. What I am trying to say is that for a single observations not all covariates included in the model are missing.

When I fit the models I get about 15% of the observations not used.

Is there an option to tell SAS to include the observations in the analysis which have at least one covariate with no missing data for the observation (to use available case analysis)? 

Thank you,

Nikos

 

 

2 REPLIES 2
ballardw
Super User

If the variables you are concerned with are CLASS variables you can use the option MISSING on the class statement to indicate that missing is considered a valid level in Logistic and Genmod. I don't see an equivalent for Surveylogistic though.

I don't believe there is another option if the predictor is not a class variable that might help directly.

 

 

Another option might be to impute values for the missing variables.

 

 

npandis
Fluorite | Level 6

Thank you and best wishes,

nikos

SAS INNOVATE 2024

Innovate_SAS_Blue.png

Registration is open! SAS is returning to Vegas for an AI and analytics experience like no other! Whether you're an executive, manager, end user or SAS partner, SAS Innovate is designed for everyone on your team. Register for just $495 by 12/31/2023.

If you are interested in speaking, there is still time to submit a session idea. More details are posted on the website. 

Register now!

What is Bayesian Analysis?

Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.

Find more tutorials on the SAS Users YouTube channel.

Get the $99 certification deal.jpg

 

 

Back in the Classroom!

Select SAS Training centers are offering in-person courses. View upcoming courses for:

View all other training opportunities.

Discussion stats
  • 2 replies
  • 577 views
  • 0 likes
  • 2 in conversation