@article{ref1,
title="Time-to-event analysis for sports injury research part 1: time-varying exposures",
journal="British journal of sports medicine",
year="2019",
author="Nielsen, Rasmus Oestergaard and Bertelsen, Michael Lejbach and Ramskov, Daniel and Møller, Merete and Hulme, Adam and Theisen, Daniel and Finch, Caroline F. and Fortington, Lauren Victoria and Mansournia, Mohammad Ali and Parner, Erik Thorlund",
volume="53",
number="1",
pages="61-68",
abstract="BACKGROUND: <i>'How much change in training load is too much before injury is sustained, among different athletes?'</i> is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology. <br><br>AIM: To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes. CONTENT: Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. <br><br>CONCLUSION: To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data.<br><br>© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.<p /> <p>Language: en</p>",
language="en",
issn="0306-3674",
doi="10.1136/bjsports-2018-099408",
url="http://dx.doi.org/10.1136/bjsports-2018-099408"
}