Applying Zero-inflated Mixed Model to School Absenteeism Surveillance in Rural China

Authors

  • Xiaoxiao Song School of Public Health, Fudan University, Shanghai, CHINA
  • Tao Tao School of Public Health, Fudan University, Shanghai, CHINA
  • Qi Zhao School of Public Health, Fudan University, Shanghai, CHINA
  • Fuqiang Yang Provincial Center for Disease Prevention and Control, nanchang, Jiangxi, CHINA
  • Palm Lars Future Position X, Gavle, SWEDEN
  • Diwan Vinod ICHAR, Karolinska Instituet, Stockholm, SWEDEN
  • Hui Yuan Jiangxi Provincial Center for Disease Prevention and Control, nanchang, Jiangxi, CHINA
  • Biao Xu School of Public Health, Fudan University, Shanghai, CHINA

DOI:

https://doi.org/10.5210/ojphi.v5i1.4421

Abstract

Absenteeism has great advantages in promoting the early detection of epidemics. Distribution of the data generally are asymmetry, zero inflation, truncation and non-independence. In order to handle these encumbrances, we should apply the Zero-inflated Mixed Model (ZIMM).

Author Biography

Xiaoxiao Song, School of Public Health, Fudan University, Shanghai, CHINA

Song xiaoxiao, Ph.D. student, is now studying in the Department of epidemiology, School of Public Health, Fudan university. At the moment my applications of interest focus on particularly practicing the longitude data, mixed model and Structural Equation Models (SEM), as well as Multilevel models in public health and medical research.

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Published

2013-03-23

How to Cite

Song, X., Tao, T., Zhao, Q., Yang, F., Lars, P., Vinod, D., … Xu, B. (2013). Applying Zero-inflated Mixed Model to School Absenteeism Surveillance in Rural China. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4421

Issue

Section

Oral Presentations: Temporal or Spatio-temporal