title: Recommendations for presenting analyses of effect modification and interaction.
abstract: Authors often do not give sufficient information to draw conclusions about the size and statistical significance of interaction on the additive and multiplicative scales. To improve this, we provide four steps, template tables and examples. We distinguish two cases: when the causal effect of intervening on one exposure, across strata of another factor, is of interest ('effect modification'); and when the causal effect of intervening on two exposures is of interest ('interaction').  Assume we study whether X modifies the effect of A on D, where A, X and D are dichotomous. We propose presenting: (i) relative risks (RRs), odds ratios (ORs) or risk differences (RDs) for each (A, X) stratum with a single reference category taken as the stratum with the lowest risk of D; (ii) RRs, ORs or RDs for A within strata of X; (iii) interaction measures on additive and multiplicative scales; (iv) the A-D confounders adjusted for. Assume we study the interaction between A and B on D, where A, B and D are dichotomous. Steps (i) and (iii) are similar to presenting effect modification. (ii) Present RRs, ORs or RDs for A within strata of B and for B within strata of A. (iv) List the A-D and B-D confounders adjusted for. These four pieces of information will provide a reader the information needed to assess effect modification or interaction. The presentation can be further enriched when exposures have multiple categories. Our proposal hopefully encourages researchers to present effect modification and interaction analyses in as informative a manner as possible.
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands. m.j.knol@umcutrecht.nl
authors.forename: Mirjam J
authors.initials: MJ
authors.lastname: Knol
authors.forename: Tyler J
authors.initials: TJ
authors.lastname: VanderWeele
mesh_terms: D015984:Causality; D015987:Effect Modifier, Epidemiologic; D016021:Epidemiologic Studies; D006801:Humans; D015233:Models, Statistical; D012307:Risk Factors