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      On time series analysis of public health and biomedical data.

      1 , ,

      Annual review of public health

      Annual Reviews

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          Abstract

          This paper gives an overview of time series ideas and methods used in public health and biomedical research. 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 most commonly used in regression analysis to describe the dependence of the response at each time on predictor variables including covariates and possibly previous values in the series. For example, Bell et al. ( 2 ) use time series methods to regress daily mortality in U.S. cities on concentrations of particulate air pollution. Time series methods are necessary to make valid inferences from data by accounting for the correlation among repeated responses over time.

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          Most cited references 35

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          Generalized linear models (Second edition).

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            Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation

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              Simple mathematical models with very complicated dynamics.

               Bennett May (1976)
              First-order difference equations arise in many contexts in the biological, economic and social sciences. Such equations, even though simple and deterministic, can exhibit a surprising array of dynamical behaviour, from stable points, to a bifurcating hiearchy of stable cycles, to apparently random fluctuations. There are consequently many fascinating problems, some concerned with delicate mathematical aspects of the fine structure of the trajectories, and some concerned with the practical implications and applications. This is an interpretive review of them.
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                Author and article information

                Affiliations
                [1 ] Department of Biostatistics, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland 21205, USA. szeger@jhsph.edu
                Journal
                Annu Rev Public Health
                Annual review of public health
                Annual Reviews
                0163-7525
                0163-7525
                2006
                : 27
                10.1146/annurev.publhealth.26.021304.144517
                16533109

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