ABSTRACT
The landscape of leadership for women has transformed over the last century, but leadership opportunities for women are still far from being equal to men (Kellerman and Rhode, 2007). In statistics and biostatistics departments/divisions across the world, the situation is no better. This article focuses on the issue of underrepresentation of women statisticians leading large-scale collaborative projects (primarily in biomedicine and public health), the challenges associated with taking on such roles, and what can be done to address those challenges. It is a general theoretical belief that any workplace will ideally benefit from a woman’s values, needs, and life experiences being reflected in decision-making positions, but it is a fact that decision-making bodies are mostly dominated by men (O’Connor, 2007). The style of successful leadership is often found to be different for men and women. While a self-asserting, threatening style may work well for a male leader, women using an inclusive and supportive style are often perceived as more effective leaders, and this type of empathic response may be biologically more natural for women (Singer et al., 2006). Do these general stereotypical conjectures or assertions about gender-specific roles translate to the field of statistics? In particular, our focus is on large-scale collaborations that involve partnership of statisticians and nonstatisticians to tackle a question of scientific/societal relevance. Communicating and convincing the nonstatistician colleague itself can pose certain basic challenges irrespective of the gender of the statistician on a project, but in this article we explore if there is an “effect modification” by gender: namely, do the challenges and the solutions that appear to work for lead statisticians in large collaborative teams comprising of diverse scientific expertise vary by gender?
