Hello all, We have a multivariate missing data(outcome is a continuous measure and missing occurs in both outcome as well as in covariates) and the it follows the assumption of MNAR. We are trying to do the pattern mixture model approach as suggested by Little (1993) in his JASA paper. But we had some difficulty of doing that. I can briefy explain below our data structure: The data set consists of four sets of patterns: 1. Non- missing outcome(continuous measure) with all the values of the covariates are available 2. Non-missing outcome with one or more vaues of the covariates are missing 3. Missing outcome with all the values of the covariates are available
4. Missing outcome with one or more vaues of the covariates are missing. We modelled on non-missing outcome using the first two groups and estimated the parameters and using these estimated parameters, we predict the missing outcome, but for only with all the values of the covatiate. We cannot be able to find out the values for the missing outcome with missed covariate values. In this type of situation, how to model this case using the data patterns in 3 and 4. Is there any method available for the missing covarites for imputation. Any suggestions. Thanks in advance. Bala -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.utsouthwestern.edu/pipermail/impute/attachments/20041025/2964f7dc/attachment.htm From von-hippel.1 <@t> osu.edu Thu Oct 28 11:50:34 2004 From: von-hippel.1 <@t> osu.edu (Paul von Hippel) Date: Sun Jun 26 08:25:02 2005 Subject: [Impute] overloading SAS PROC MI Message-ID: <[email protected]> An HTML attachment was scrubbed... URL: http://lists.utsouthwestern.edu/pipermail/impute/attachments/20041028/9a6df394/attachment.htm From malone <@t> alumni.duke.edu Thu Oct 28 11:55:36 2004 From: malone <@t> alumni.duke.edu (Patrick S. Malone) Date: Sun Jun 26 08:25:02 2005 Subject: [Impute] overloading SAS PROC MI In-Reply-To: <[email protected]> References: <[email protected]> Message-ID: <[email protected]> On Thu, 28 Oct 2004 12:50:34 -0400, Paul von Hippel <[email protected]> wrote: > I have a data set comprising 20,000 cases. When the number of variables > is more > than 100 or so, I find that SAS PROC MI returns > > ERROR: Invalid Operation > > Has anyone else run into this. Yes. > I am using SAS 8.2. That's your problem. The limitation (which different people run into around 50-70 variables usually) was fixed by SAS 9.1. > > Thanks! > Paul von Hippel -- Patrick S. Malone, Ph.D., Research Scientist Duke University Center for Child and Family Policy North Carolina, USA http://www.duke.edu/~malone http://www.pubpol.duke.edu/centers/child/
