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.
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