Re: Stochastic Regression

Posted by Jon Peck on Mar 30, 2016; 2:36pm
URL: http://spssx-discussion.165.s1.nabble.com/Stochastic-Regression-tp5731831p5731834.html

When you run the MVA procedure with the Regression option, you have the option of adding random noise to the imputed values, which is what Enders calls stochastic regression.

From the MVA help...

Estimation Adjustment. The regression method can add a random component to regression estimates. You can select residuals, normal variates, Student's t variates, or no adjustment.

• Residuals. Error terms are chosen randomly from the observed residuals of complete cases to be added to the regression estimates.
• Normal Variates. Error terms are randomly drawn from a distribution with the expected value 0 and the standard deviation equal to the square root of the mean squared error term of the regression.
• Student's t Variates. Error terms are randomly drawn from a t distribution with the specified degrees of freedom, and scaled by the root mean squared error (RMSE).

Multiple imputation may be a better technique, but it is not available for all statistical procedures.

On Wed, Mar 30, 2016 at 8:15 AM, Salbod <[hidden email]> wrote:

I came across stochastic regression in Enders's book on missing data (page
46):

http://hsta559s12.pbworks.com/w/file/fetch/52112520/enders.applied

Can this analysis be implemented using SPSS? Is there a tutorial or article
available?

Thank you,

Steve





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