***** To join INSNA, visit http://www.insna.org ***** I am revising a paper on imputation of skewed variables. This is not a network paper, but an example using network data would be very appropriate. In particular, I'm seeking data with (at least) two repeated measures of popularity. A friendship network, say. At time one, each respondent in a group lists his or her friends, perhaps using a list, perhaps distinguishing among close friends, friends, and acquaintances. The people who get named the most are the most popular (highest indegree, perhaps with greater weight given to stronger ties). At time 2, the process is repeated. The correlation between time 1 and time 2 popularity scores is an index of stability. What I like about this example is that popularity is (likely) very skewed, and the correlation between waves 1 and 2 is (likely) very strong. Also, there are likely to be missing values if (say) some people leave or join the group between waves, or if people are inadvertently left off the list of possible nominations. So it's exactly what I need for my paper: high skew, high correlation, and missing values that need imputing. (I realize there may be unique issues in imputing network data, but those are really beyond the scope of my paper.) The Add Health data follows this format, but it's a bit of trouble to access and transform into the necessary form. Since I just need a simple example for a statistics paper, I'm seeking data sets that are smaller and ready to go. If one of you has something to share, I'd be grateful to hear about it. Many thanks and best wishes -- Paul von Hippel Paul von Hippel Department of Sociology / Initiative in Population Research Ohio State University 300 Bricker Hall 190 N. Oval Mall Columbus OH 43210 614 688-3768 Office hours TThF 3-5pm I read email every weekday at 3. _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.