level, the standard error of the intercept is underestimated whereas the standard error of
the regression coefficients associated with the covariate of the intermediate level and the
remaining crossed factor are overestimated. When the ignored crossed factor is at the
intermediate level, only the standard error of the regression coefficients associated with
the covariate of the bottom level is overestimated.
In Study Two, longitudinal multilevel data were generated mirroring studies in
which students are measured repeatedly and change schools over time. It was found that
when the school level is modeled hierarchically above the student level rather than as a
crossed factor, part of the variance at the school level is added to the student level,
causing underestimation of the school-level variance and overestimation of the studentlevel
variance and covariance. The standard errors of the intercept and the regression
coefficients associated with the school-level predictors are underestimated, which may
cause spurious significance for results.
The findings of the dissertation enhanced our understanding of the functioning of
CCREMs in both cross-sectional and longitudinal multilevel data. The findings can help
researchers to determine when CCREMs should be used and to interpret their results
with caution when they misspecify CCREMs.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-1423 |
| Date | 15 May 2009 |
| Creators | Zheng, Yangxing |
| Contributors | Giese, Benjamin S., North, Gerald R. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | electronic, application/pdf, born digital |
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