One of the sources of inaccuracy in parameter estimates of multilevel models is omitted variable bias, caused by the omission of an important predictor. The purpose of this study was to examine the performance of six estimation procedures in estimating the fixed effects when a level-2 interaction term was omitted from a two-level hierarchical linear model. Four alternative estimators (FE, WLS1, WLS2, WLS3) based on the work of Frees (2001) and the Maximum Likelihood (FML, ReML) estimation methods were examined. Findings of the Monte Carlo study revealed that the FML and ReML methods were the least biased methods when a level-2 interaction was omitted from the multilevel model. FML and ReML produced the lowest RMSD values of all six estimation methods regardless of level-2 sample size, ICC, or effect sizes of the level-2 variables. The difference in the performance of the alternative and Maximum Likelihood (ML) procedures diminished as level-2 sample size and ICC increased. The bias in all six estimation methods did not differ much when the effect sizes of the level-2 predictors varied. When the methods were examined using the ECLS data, the results of the Monte Carlo study were confirmed. The ML methods were the least biased of all the methods when a level-2 interaction term was omitted from the model.
| Identifer | oai:union.ndltd.org:PITT/oai:PITTETD:etd-11272007-104235 |
| Date | 29 January 2008 |
| Creators | Terhorst, Lauren |
| Contributors | Suzanne Lane, Kevin H. Kim, Heather J. Bachman, Elizabeth Votruba-Drzal, Feifei Ye |
| Publisher | University of Pittsburgh |
| Source Sets | University of Pittsburgh |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.pitt.edu/ETD/available/etd-11272007-104235/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Pittsburgh or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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