Determine power and sample size for the simple and mediation Actor–Partner Interdependence Model

Abstract Objective We provide details on how relationship researchers can use Monte Carlo simulation for power estimation and sample size determination for the simple and the mediation Actor–Partner Interdependence Model (APIM). In addition to power estimates for specific sample sizes, we show how the sample size for each effect can be determined. Background Researchers designing a study commonly want to know what sample size is required to detect a specific effect or in the case after data collection is completed what the power is for a specific effect. Method The solution we present asks for the correlations among the variables and allows for the specification of skewness and kurtosis and the incorporation of missing data. For the mediation APIM, power is estimated for the direct effects, indirect effects, and total effects. Results The illustrations demonstrate that indistinguishable members require sample sizes that are about half of the sample sizes required for distinguishable members and that skewed data tend to require larger sample sizes. The illustration of the mediation APIM reveals that it is not uncommon that some of the simple indirect effects are significant, but none of the total indirect effects and none of the total effects are. Conclusion Monte Carlo simulation provides an easy‐to‐use and flexible solution to determine power and sample sizes for the simple and mediation APIM for distinguishable and indistinguishable members. Implications Recommendations are made for dyadic studies with small sample sizes and studies using the mediation APIM.