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BMC Medical Research Methodology

, 6:16

First Online: 03 April 2006Received: 12 September 2005Accepted: 03 April 2006

Abstract

BackgroundIntervention time series analysis ITSA is an important method for analysing the effect of sudden events on time series data. ITSA methods are quasi-experimental in nature and the validity of modelling with these methods depends upon assumptions about the timing of the intervention and the response of the process to it.

MethodThis paper describes how to apply ITSA to analyse the impact of unplanned events on time series when the timing of the event is not accurately known, and so the problems of ITSA methods are magnified by uncertainty in the point of onset of the unplanned intervention.

ResultsThe methods are illustrated using the example of the Australian Heroin Shortage of 2001, which provided an opportunity to study the health and social consequences of an abrupt change in heroin availability in an environment of widespread harm reduction measures.

ConclusionApplication of these methods enables valuable insights about the consequences of unplanned and poorly identified interventions while minimising the risk of spurious results.

AbbreviationsAICAkaike Information Criterion

ARIMAAuto-regressive Integrated Moving Average

IDRSIllicit Drug Reporting System

IDUInjecting Drug Users

ITSAIntervention time series analysis

KIKey Informant

Electronic supplementary materialThe online version of this article doi:10.1186-1471-2288-6-16 contains supplementary material, which is available to authorized users.

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Autor: Stuart Gilmour - Louisa Degenhardt - Wayne Hall - Carolyn Day

Fuente: https://link.springer.com/







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