Modeling Spatial Heterogeneity with Excess Zeroes from School Absenteeism dSata

How to Cite

Song, X., Zhao, Q., Zhou, C., Tao, T., Palm, L., Diwan, V., Yuan, H., & Xu, B. (2015). Modeling Spatial Heterogeneity with Excess Zeroes from School Absenteeism dSata. Online Journal of Public Health Informatics, 7(1).


Absenteeism has great advantages in promoting the early detection of epidemics. The spatial patterns of the data generally are polytropy and heterogeneity. The public health experts pay more attention to whether an outbreak will happen or/and how large the epidemic will be of school absenteeism data in spatial patterns. We construct simultaneously two set of random effects (u1, u2) in RE-ZIP to quantify this two kind spatial heterogeneity for 62 schools.
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