The purpose of this paper was to introduce the theory of "Hierarchical-Linear Model" ( HLM). The authors also gave a analysis of real data. By this way, the reader will realize the application of HLM.
First, in this paper, we introduced the different names of HLM in other research area. Besides this, the software of HLM was be introduced.
Second, we explain the theory of HLM. In addition to the "full model", of HLM, we also raised five submodels of HLM, which were "one-way DANOVA with random effects", "means-as-outcomes regression", "one-way ANCOVA with random effects", "random coefficients regression model", and "a model with nonrandomly varying slopes". In this paper, the assumption, characteristics, and application of the above five submodels were be discussed.
Finally, we analyzed the data, which was from the plan of NSC, and explained the results. From the analysis we gave some suggestions for further research.
| Keywords: | Hierarchical Linear Models; Covariance Components Model; Nature Science Achievement |
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