Literature DB >> 8743077

Structural time series models in medicine.

A Harvey1, S J Koopman.   

Abstract

Structural time series models are formulated in terms of components, such as trends, seasonals and cycles, which have a direct interpretation. This article describes such models and gives examples of how they can be applied in medicine. Univariate models are considered first, and then extended to include explanatory variables and interventions. Multivariate models are then shown to provide a framework for modelling longitudinal data and for carrying out intervention analysis with control groups. The final sections deal with data irregularities and non-Gaussian observations.

Mesh:

Year:  1996        PMID: 8743077     DOI: 10.1177/096228029600500103

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  3 in total

1.  Evaluation of the impact on human salmonellosis of control measures targeted to Salmonella Enteritidis and Typhimurium in poultry breeding using time-series analysis and intervention models in France.

Authors:  E Poirier; L Watier; E Espie; F-X Weill; H De Valk; J-C Desenclos
Journal:  Epidemiol Infect       Date:  2007-11-30       Impact factor: 2.451

2.  Respiratory infection and otitis media visits in relation to pneumococcal conjugate vaccine use in Saskatchewan.

Authors:  Ngoc-Hang Khuc; Ben Tan; Rosalie Tuchscherer; Nigel Sb Rawson; Philippe De Wals
Journal:  Can J Infect Dis Med Microbiol       Date:  2013       Impact factor: 2.471

3.  The promise of the state space approach to time series analysis for nursing research.

Authors:  Janet A Levy; Heather E Elser; Robin B Knobel
Journal:  Nurs Res       Date:  2012 Nov-Dec       Impact factor: 2.381

  3 in total

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