The literature on the impact of expansive poses on biological and psychological variables is characterized by discrepant findings. These discrepant findings may, in part, be a function of differences in how data were analyzed. In this article, we use multiverse analysis to examine whether the findings reported in the original paper by Carney, Cuddy, and Yap are robust to plausible alternative data analytic specifications: outlier identification strategy, the specification of the dependent variable, and the use of control variables. Our findings indicate that the inferences regarding the presence and size of an effect on testosterone and cortisol are highly sensitive to data analytic specifications. We encourage researchers to routinely explore the influence of data analytic choices on statistical inferences and also encourage editors and reviewers to require explicit examinations of the influence of alternative data analytic specifications on the inferences that are drawn from data.