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Doctoral Dissertation Announcement
Candidate: Oluwagbohunmi Adetunji Awosoga
Doctor of Philosophy
Title: Meta Analyses of Multiple Baseline Time Series Design Intervention Models for Dependent and Independent Series
Dr. Joseph W. McKean, Chair
Dr. Jung C. Wang
Dr. Bradley E. Huitema
Date: Wednesday, April 8, 2009 4:00 p.m. - 6:00 p.m.
6625 Everett Tower
This study develops a traditional meta-type analysis for multiple baseline series. Robust methodology for multiple baseline series is also developed. The procedures are almost as efficient as the traditional method on “good” data and are generally much more efficient on data containing outliers. The diagnostic procedures for the analysis of these data are also developed. The design matrices provided for the two-phase (AB) design which allow for change in level and change in slope between each phase and the subsequent phase. Similarly, our methodology can be extended to more than two phased time series design intervention models. Our parametric procedures are based on least squares (LS) estimation. The robust procedures are similar to the parametric procedures except another norm rather than the Euclidean norm is used. Illustrative examples are discussed. A Monte Carlo study of the methods is provided. The study investigates the validity of the procedures and power comparisons between the parametric and robust methods.