"Missing Data: Analysis and Design in Psychological Trauma Research"

The presentation will be in two parts. In Part 1, I will discuss theory and practice in missing data analysis, and will provide a brief demonstration of two acceptable approaches to analysis with missing data: multiple imputation and full-information maximum likelihood (FIML) with structural equation modeling. In Part 2, I will present two kinds of planned missing data designs that may be useful in trauma research. One design, called the 3-form design, is a member of a family of designs that can improve the efficiency of one's survey measurement. By building in some missingness by design, the researcher can actually test more hypotheses with reasonable power. Scenarios relevant to trauma research are presented to illustrate the benefits of the design. The second design involves the use of two methods of measurement. One method is an inexpensive, but less valid, measure of the construct of interest, and is typically administered to a large number of respondents; the second method is an expensive and more valid measure of the construct that is administered only to a subset of the respondents. The potential benefits of the procedure are illustrated with a trauma-relevant example. The presention will conclude with a question and answer session.