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Distributions and what to do when they are non-normal

Alan Taylor
Med J Aust 2018; 208 (1): 1013. || doi: 10.5694/mja16.01255
Published online: 15 January 2018

Medical researchers often want to find out how medically relevant outcomes are related to other factors. To do so, they carry out analyses and fit models that are based on assumptions about the nature of the research data. This article describes three methods which may be used when one commonly made assumption is not met. The methods are demonstrated on a real dataset in which the outcome is an index of harmful use of alcohol, with higher scores indicating a higher incidence of harmful behaviours. The frequency distribution of the outcome, alc_harm, is shown in Box 1.

  • Alan Taylor

  • Macquarie University, Sydney, NSW

Correspondence: alan.taylor@mq.edu.au

Acknowledgements: 

I thank Dr Lesley Inglis for her careful editing and suggestions, Professor Michael Jones for his advice and encouragement, and Babucarr Sowe for allowing me to use his data.

Competing interests:

No relevant disclosures.

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