Abstract Concerns have been raised about the use of single host- or home-country samples in analyzing the effects of cultural distance (CD). That is, the estimated effects of CD may be confounded with those of the underlying cultural dimensions or other contextual factors correlated with CD. This study reassesses the risk of confounding when using single-country samples through simulation analyses conducted under various conditions, including different sample sizes and structures, within- and between-country variances, and analysis methods. The results indicate that when other cultural or contextual variables related to the outcome are also included and multilevel modeling is applied, the risk of confounding is not significant across diverse settings. The problem of confounding becomes significant only when using ordinary least squares, which does not take into account the potential nonindependence of observations in hierarchical data. However, in multilevel analyses using single-country samples, statistical power may become insufficient when controlling for cultural variables correlated with CD, particularly when the effect size of CD is small. To address this issue, we present a statistical technique that researchers can use to identify potential confounders and provide guidelines on the sample size required to maintain adequate power.
Kim et al. (Wed,) studied this question.