Ocean heat transport in a Simple Ocean Data Assimilation (SODA): structure, mechanisms, and impacts on climate
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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.
Zheng, Yangxing (2007). Ocean heat transport in a Simple Ocean Data Assimilation (SODA): structure, mechanisms, and impacts on climate. Doctoral dissertation, Texas A&M University. Available electronically from