Bovaird presents as part of research methodologies series Jan. 27

23 Jan 2012    

Not All Students Need to be Assessed: Research Designs Where Data are Intentionally Missing
Friday, Jan. 27, 11:30 a.m. - 1:00 p.m.
265 Mabel Lee Hall

It can be daunting, difficult, or outright impossible to gain access to adequately large participant samples in order to test research hypotheses under conventional thinking. This talk will outline research design decisions that may enable researchers to answer important questions with smaller assessment batteries or smaller sample sizes than what may traditionally be recommended. Several practical examples will be presented to illustrate two broad scenarios: All participants are assessed, but not on all instruments; or all participants are assessed on all instruments, but not all participants initially anticipated actually participate. The literature bases on planned missing data designs and sequentially designed experiments will be used to support empirical examples of potential resource savings.

Bovaird earned his doctorate in Quantitative Psychology from the University of Kansas in 2002. He currently serves as Associate Professor of Quantitative, Qualitative and Psychometric Methods in Educational Psychology at the University of Nebraska–Lincoln and Director of the CYFS Statistics and Research Methodology Unit. His research interests involve determining the proper use of latent variable methods—including structural equation modeling, item response theory, and multilevel modeling—and applying these methods to advance substantive research in the social and behavioral sciences.