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S. W. Raudenbush, A. S. Bryk and Z. G. Guo, “Hierarchical Linear Models: Application and Data Analysis Method,” Beijing: Social Sciences Academic Press, 2007, pp. 83-90.

has been cited by the following article:

• TITLE: Hierarchical Linear Model of Monthly Rainfall with Regional and Seasonal Interaction Effects

  AUTHORS: Yonghua Zhu, Hongtao Lu, Zilin Zhu

  KEYWORDS: Monthly Rainfall; Hierarchical Linear Model; Regional Effects; Interaction Effect Component

  JOURNAL NAME: American Journal of Computational Mathematics, Vol.3 No.3B, October 24, 2013

  ABSTRACT: According to the hierarchical characteristics of monthly rainfall in different regions, the paper takes the geographical factors and seasonal factors into the hierarchical linear model as the level effect. Through clustering methods we select two more representative regional meteorological data. We establish three-layer model by transforming the interactive structure date into nested structure data. According the model theory we perform the corresponding model calculations, optimization and analysis, accordingly to interpret the level effects, and residual test. The results show that most of the difference in Monthly Rainfall was respectively explained by Variables (Meteorological factors, seasonal effects, geographic effects) in different levels.