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Statistical control of extraneous (i.e., third) variables is a common analytic tool among leadership researchers. While such a strategy is typically assumed to prove beneficial, it can actually introduce various complications that are underestimated or even ignored. This study investigates and summarizes the current state of control variable usage in leadership research by qualitatively and quantitatively examining the use of statistical control variables in 10 highly regarded management and applied psychology journals. Despite available “best practices,” our results indicate that control variable usage in existing leadership studies is rarely grounded in theory but instead frequently relies on outdated misconceptions. Moreover, a meta-analysis of the relationships between popular control variables and leadership constructs finds nearly universal weak effect sizes, suggesting that many studies may not only be losing valuable degrees of freedom but also making inferences based on biased parameter estimates. To address these issues, we put forth a number of recommendations to assist leadership scholars with determining whether potential third variables should be controlled for in their leadership research.

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Organizational climate research has surged recently, but the disbursement of research contributions across domains has made it difficult to draw conclusions about climate and its connections with performance. To make sense of the climate literature, we used the competing values framework (CVF) to classify domain-specific climates into four climate types (clan, adhocracy, hierarchy, and market climates). We did so by conceptually linking domain-specific climates that are manifestations of the same underlying strategic values. We then conducted meta-analyses to examine the magnitudes, mechanisms, and moderators of the individual and group-level associations between the CVF climates and performance. These meta-analyses revealed positive climate–performance associations for each climate type and supported job attitudes as a common mediator. We also examined several methodological moderators of climate–performance relationships, testing the source of climate and performance measures, the temporal assessment of these constructs, and the level of within-group agreement in climate measures as possible boundary conditions.