We test this hypothesis in column (2) by including interaction terms between tenure and the dummies for firm size.
We examined effect measure modification of the exposure outcome relationship due to participant demographic factors by including interaction terms of exposure (volunteering) and participant age, sex, and race.
Note also that by including interaction terms of the type (a j ⋅ Z i ), marginal utility and hence the marginal rate of substitution can be made to depend on an individual characteristic (for an application to individuals with and without chronic conditions, see e.g. Mc Neil Vroomen & Zweifel 2011 [4]).
We tested for effect modification by age (dichotomized: <60 years vs. > = 60 years) and gender by including interaction terms in the models for each of the four dependent variables.
Fourth, we considered whether the pooled analysis was overly simplistic in not considering effect modification of the IPV-HIV relationship by country, by including interaction terms between the IPV exposure measures and country fixed effects; we tested for homogeneity of IPV -country effects using a Wald-type F-test for the joint probability of no interaction.
We tested interactions between variables by including interaction terms.
Interaction tests were also conducted by including interaction terms between independent variables.
Third, we tested for heterogeneity of within-district slopes across districts by including interaction terms.
32 We evaluated statistically significant effect modification by including interaction terms in the models.
Interaction was tested by including interaction terms in the Cox proportional hazards analysis.
We tested heterogeneity of effects by stratification and by including interaction terms in regression models.
