On Time Series Analysis of Public Health and Biomedical Data
AbstractA 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.
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Bibliographic InfoPaper provided by Berkeley Electronic Press in its series Johns Hopkins University Dept. of Biostatistics Working Paper Series with number 1054.
Date of creation: 03 Sep 2004
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Stochastic process; Smoothing; Autocorrelation; Periodogram; Spectrum; Regression; Autoregressive model; ARMA; Non-linear time series;
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