Analysing imputed data in PROCESS

#1
Hi - hoping for some help.

In my dataset I have used the regression method to impute missing data. My issue now is that I need to analyse this data using the PROCESS plugin. What is the best way to create a pooled dataset that I can use in PROCESS? I feel as though aggregating by taking a mean of imputed scores isn't the right way to go...

Cheers :)
 

spunky

Doesn't actually exist
#2
You do not average imputed datasets. What you work on is parameter estimates, never on the actual data. Like you fit your mediation model in dataset #1, then again in dataset #2, then again in dataset #3 where there are as many datasets as there were imputations. Once you do that you use Rubin's rules to combine the parameter estimates and obtain their variance. Getting the point-estimates of the parameters is easy (you just take the average of regression coefficients, for instance). Getting the right variance (i.e. standard error) for those estimates is a little more complicated because you need to calculate both within-imputation variance and between-imputation variance.

If you were using another software (R or STATA) they do that for you. SPSS (or the PROCESS macro) cannot handle it.
 

hlsmith

Not a robit
#3
That is exactly how I figured you would do it Spunky. I haven't done it in mediation analysis before, so I was too bashful to recommend it.