Jos W R Twisk1, Nynke Smidt, Wieke de Vente. 1. Department of Clinical Epidemiology and Biostatistics and EMGO-institute, Vrije Universiteit medical centre, Vd Boechorststraat 7, 1081 BT Amsterdam, Netherlands. JWR.Twisk@vumc.nl
Abstract
STUDY OBJECTIVE: The purpose of this paper is to give an overview and comparison of different easily applicable statistical techniques to analyse recurrent event data. SETTING: These techniques include naive techniques and longitudinal techniques such as Cox regression for recurrent events, generalised estimating equations (GEE), and random coefficient analysis. The different techniques are illustrated with a dataset from a randomised controlled trial regarding the treatment of lateral epicondylitis. MAIN RESULTS: The use of different statistical techniques leads to different results and different conclusions regarding the effectiveness of the different intervention strategies. CONCLUSIONS: If you are interested in a particular short term or long term result, simple naive techniques are appropriate. However, if the development of a particular outcome is of interest, statistical techniques that consider the recurrent events and additionally corrects for the dependency of the observations are necessary.
STUDY OBJECTIVE: The purpose of this paper is to give an overview and comparison of different easily applicable statistical techniques to analyse recurrent event data. SETTING: These techniques include naive techniques and longitudinal techniques such as Cox regression for recurrent events, generalised estimating equations (GEE), and random coefficient analysis. The different techniques are illustrated with a dataset from a randomised controlled trial regarding the treatment of lateral epicondylitis. MAIN RESULTS: The use of different statistical techniques leads to different results and different conclusions regarding the effectiveness of the different intervention strategies. CONCLUSIONS: If you are interested in a particular short term or long term result, simple naive techniques are appropriate. However, if the development of a particular outcome is of interest, statistical techniques that consider the recurrent events and additionally corrects for the dependency of the observations are necessary.
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