On Time Series Analysis of Public Health and Biomedical Data


Autoria(s): Zeger, Scott L.; Irizarry, Rafael A; Peng, Roger D.
Data(s)

01/09/2004

Resumo

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.

Formato

application/pdf

Identificador

http://biostats.bepress.com/jhubiostat/paper54

http://biostats.bepress.com/cgi/viewcontent.cgi?article=1054&context=jhubiostat

Publicador

Collection of Biostatistics Research Archive

Fonte

Johns Hopkins University, Dept. of Biostatistics Working Papers

Palavras-Chave #Stochastic process #Smoothing #Autocorrelation #Periodogram #Spectrum #Regression #Autoregressive model #ARMA #Non-linear time series #Longitudinal Data Analysis and Time Series
Tipo

text