The announcement below is posted on behalf of Dr. Jenn-Yun Tein ([email protected]).
The Arizona State University Program for Prevention Research is hiring a postdoctoral Research Associate for NIMH funded projects to evaluate a long-term intervention for bereaved children and apply advanced methodologies in prevention research, particularly as applied to studies of program effectiveness and dissemination. This position will assist faculty with the application of advanced methodologies in prevention research, methodological development and the writing of manuscripts, and conduct statistical analyses with structural equation modeling, longitudinal modeling techniques and multilevel modeling. Required Qualifications: PhD in Psychology, Sociology, Education or other social science discipline. Experience with advanced statistical analyses, including structural equation modeling, longitudinal modeling techniques and multilevel modeling. Desired Qualifications: Experience with advanced statistical applications. Experience supervising others. Application procedure: fax or mail letter of interest, curriculum vitae, and three letters of reference to Dr. Jenn-Yun Tein, Program for Prevention Research, Arizona State University, P. O. Box 876005, Tempe, AZ 85287-6005. Application Deadline: November 30, 2005, or if not filled, every two weeks thereafter until search closed. This is a 2 year position and includes allotted time to take advanced statistical seminars. Salary range: $45,000-$50,000. Background check will be conducted prior to employment. AA/EOE. ------------------------------------------------ Scott R. Weaver, Ph.D. Postdoctoral Research Fellow Program for Prevention Research Arizona State University P.O. Box 876005 Tempe, AZ 85287-6005 (480) 727-6155 (O) (480) 965-5430 (F) -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.utsouthwestern.edu/pipermail/impute/attachments/20051109/5416a363/attachment.htm From Craig.Enders <@t> asu.edu Fri Nov 11 19:34:43 2005 From: Craig.Enders <@t> asu.edu (Craig Enders) Date: Fri Nov 11 19:34:49 2005 Subject: [Impute] MI with multiple cohort data Message-ID: <[email protected]> I'm curious if anyone has used MI to handle missing data by design in a longitudinal study with multiple age cohorts - the ultimate goal is to perform a growth curve analysis, e.g., using PROC MIXED.? Because certain individuals were never assessed at particular ages, it seems that both age (the "time score") and the outcome is missing.? Some of the outcome scores are missing by design (e.g., someone in the 15 year old cohort was never assessed at age 13), and some of the outcome scores are missing for other reasons (e.g., attrition occurred within each cohort).? It seems that there are at least three different options: 1) Impute the time scores (i.e., the ages that the subjects were never assessed at due to the missing by design data collection strategy) and the missing outcome values.? This solution makes me very uneasy. 2) Fill in the missing time scores with age values that could have hypothetically been observed, had the data collection schedule used a single cohort, then impute the missing outcome scores - this seems like a better solution, and would result in a fully balanced data set. 3) Use MI to fill in missing outcome scores separately within each age cohort - this doesn't seem to provide any advantage over ML estimation using PROC MIXED, sans the imputation phase. Obviously, the growth curve model could be estimated using PROC MIXED, but it would be useful to incorporate auxiliary variables that might be related to attrition.? The auxiliary variable issue is straightforward if ML estimation is implemented using SEM software (e.g., Graham, 2003), but I'm curious about the application of MI in this situation. I would appreciate hearing different thoughts on this, Craig Enders ***************************************************************************** Dr. Craig Enders Assistant Professor Quantitative Psychology Concentration Department of Psychology Arizona State University Box 871104 Tempe, AZ 85287-1104 Office?(480) 727-0739 [email protected] http://www.asu.edu/clas/psych/people/faculty/cenders.htm ***************************************************************************** ***************************************************************************** Dr. Craig Enders Assistant Professor Quantitative Psychology Concentration Department of Psychology Arizona State University Box 871104 Tempe, AZ 85287-1104 Office?(480) 727-0739 [email protected] http://www.asu.edu/clas/psych/people/faculty/cenders.htm *****************************************************************************
