Dear Jon,
In my experience multiple imputation can lead to unreliable results when statistical assumptions are not fulfilled (ie missing not at random), the sample is small (ie sample size less than 300 - 400) and the percent missing is large (ie gt 10%). It would be best to carefully read up on the statistical assumptions for either approach (for example in SAS documentation) and report in the paper, which approach was applied and why. Kind regards, Annette www.cai.org<http://www.cai.org> ________________________________ From: Impute -- Imputations in Data Analysis [[email protected]] on behalf of Jonathan Mohr [[email protected]] Sent: 28 March 2014 07:34 To: [email protected] Subject: Impute invalid data? I'm writing with a question about a small sample longitudinal study where the main outcome variable is level of C-reactive protein (CRP) measured at age 30 (which is the most recent time point for which data were collected). Typically, scores above a certain level are thrown out as invalid because the high level often indicates that the person has an infection. The folks who have been doing the main data analysis simply dropped cases with unacceptably high CRP levels. However, my sense is that a better strategy might be to simply score such participants' CRP scores as missing, and then conduct analyses with multiple imputation. I suggested this approach, and the main analyst stated that it "seems odd to me to impute CRP values for people in the first place, but to impute values for participant who actually had values that we then discarded and are now imputing seems even weirder. Maybe statistically there's no issue with doing that, but conceptually it just seems odd." I'm writing to see what folks on this list think. I'm certainly open to arguments for listwise deletion, but I'm not currently seeing a reason to do so given that all other data from the "high CRV" participants at earlier time points appear to be valid. Thanks in advance for your thoughts! Jon -- ***Please note change of email to [email protected]<mailto:[email protected]>*** Jonathan Mohr Assistant Professor Department of Psychology Biology-Psychology Building University of Maryland College Park, MD 20742-4411 Office phone: 301-405-5907 Fax: 301-314-5966 Email: [email protected]<mailto:[email protected]>
