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The use of multilevel modeling and the level two residual file to explore the relationship between middle years programme student performance and diploma programme student performance |
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| Affiliation: | 1. New York University, United States;2. University of California, Berkeley, United States;3. University of North Carolina – Chapel Hill, United States;1. University of Michigan, Survey Research Center, 426 Thompson Street, Ann Arbor, MI 48104-2321, United States;2. University of North Carolina, Carolina Population Center, 123 West Franklin Street, Chapel Hill, NC 27516-2524, United States;1. Department of Criminal Justice, Social Work and Legal Specialties, Central China Normal University, University of Toledo, United States;2. Department of Criminal Justice, Wayne State University, United States |
| Abstract: | Multilevel modeling has recently found a substantial niche in the context of educational research, although several details about the methodological application of these models have yet to be explored in an achievement data framework. This paper makes use of data provided by the International Baccalaureate (IB) in order to investigate modeling decisions and certain applications of the level two residual file in an effort to increase understanding about the way linear and logistic multilevel models function. The focus of this research is on the relationship between performances in two IB programmes: the Middle Years Programme (MYP) and the Diploma Programme (DP). The impact of predictors on the interpretation of the unconditional and conditional variance-covariance matrix as well as the reliability coefficients is discussed. Empirical findings suggest that students who perform better during MYP moderation tend to perform better on DP exams. |
| Keywords: | Multilevel modeling Unconditional error covariance Conditional error covariance Contextual effects Reliability coefficients Tau matrix |
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