[amelia] Re: MI question

To whom it may concern, I wrote a while back to ask about using MI, much in the same way that Scheve (2006) did in recent SAPD paper in which he imputed data for a variable that was not observed in the dataset of interest. Here's the question. I'm attempting to expmine the effects of mental health on politics. It's a revisitation of some of Lasswell's work. As you know, there's nothing in the way of data on this. So, I'm trying to use MI as a temporary solution. I plan to use data from a national survey on mental health, the National Comorbidity Study, to fill in the "missingness" within the NES for depression, anxiety, and PTSD. The problem is that there are only 30 variables, all of which are demographic in some way, that overlap between the two datasets and can be used as information. Moreover, when I tried to predict depression, anxiety, and PTSD in the NCS, the r-squares average .05. Perhaps this has something to do with the fact that the NCS has 9K observations and over 1K variables. That said, I'm concerned that once imputed into the NES the mental health items will be too noisy to predict anything. Is this something about which I need to be concerned, i.e., the low explained variances? Any advice is welcomed. Best, Christopher