In the social sciences, many quantitative research findings as well as presentations of demographics are related to participants' gender. Most often, gender is represented by a dichotomous variable with the possible responses of woman/man or female/male, although gender is not a binary variable. It is, however, rarely defined what is meant by gender. In this article, we deconstruct the concept 'gender' as consisting of several facets, and argue that the researcher needs to identify relevant aspects of gender in relation to their research question. We make a thorough exposition of considerations that the researcher should bear in mind when formulating questions about each facet, in order to exemplify how complex this construct is. We also remind the researcher that gender is not a binary category and discuss challenges in the balance between taking existing gender diversity into account and yet sorting participants into gender categorisations that function in statistical analyzes. To aid in this process, we provide an empirical example on how gender identity may be categorised when using a free-text response. Lastly, we suggest that other measurements than participants' gender might be better predictors of the outcome variable.