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On Time Series Analysis of Public Health and Biomedical Data

Author

Listed:
  • Scott Zeger

    (The Johns Hopkins Bloomberg School of Public Health)

  • Rafael Irizarry

    (Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics)

  • Roger Peng

    (Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics)

Abstract

A time series is a sequence of observations made over time. Examples in public health include daily ozone concentrations, weekly admissions to an emergency department or annual expenditures on health care in the United States. Time series models are used to describe the dependence of the response at each time on predictor variables including covariates and possibly previous values in the series. Time series methods are necessary to account for the correlation among repeated responses over time. This paper gives an overview of time series ideas and methods used in public health research.

Suggested Citation

  • Scott Zeger & Rafael Irizarry & Roger Peng, 2004. "On Time Series Analysis of Public Health and Biomedical Data," Johns Hopkins University Dept. of Biostatistics Working Paper Series 1054, Berkeley Electronic Press.
    • Handle: RePEc:bep:jhubio:1054
    Note: oai:bepress.com:jhubiostat-1054
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    File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1054&context=jhubiostat
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    Cited by:

    1. Michael C. Wimberly & Paolla Giacomo & Lon Kightlinger & Michael B. Hildreth, 2013. "Spatio-Temporal Epidemiology of Human West Nile Virus Disease in South Dakota," IJERPH, MDPI, vol. 10(11), pages 1-19, October.

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