Dear Imputers,

I have a multiple imputation procedure created according to some Bayesian 
model, performing

(1) random draws for the parameters theta from their observed-data posterior and

(2) random draws for the missing values Ymis according to their conditional 
predictive distribution f(Ymis|Yobs, theta) given the observed data and an 
actual draw of theta from (1).

As far as I have understood the concept of properness this procedure obviously 
is Bayesianly proper as defined by Schafer (1997) as well as it is proper in 
the sense of Rubin (1987) just by definition. Now I am no longer sure about the 
latter  -  can anybody give me a pointer?

Many thanks
Susanne

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Dr. Susanne R?ssler
Institute of Statistics and Econometrics
University of Erlangen-Nuernberg, Germany
email: [email protected]

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