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rwg is a common metric used to quantify interrater agreement in the organizational sciences. Finn developed rwg but based it on the assumption that raters’ deviations from their true perceptions are influenced by random chance only. James, Demaree, and Wolf extended Finn’s work by describing procedures to account for the additional influence of response biases. We demonstrate that organizational scientists have relied largely on Finn’s procedures, at least in part because of a lack of specific guidance regarding the conditions under which various response biases might be present. In an effort to address this gap in the literature, we introduce the concept of target-irrelevant, nonrandom forces (those aspects of the research context that are likely to lead to response biases), then describe how the familiar “5Ws and an H” framework (i.e., who, what, when, where, why, and how) can be used to identify these biases a priori. It is our hope that this system will permit those who calculate rwg to account for the effects of response biases in a manner that is simultaneously rigorous, consistent, and transparent.

We used a community surveillance system to gather information regarding pregnancy outcomes and the cause of death for women of reproductive age (WRA) in Kanchanpur, Nepal. A total of 784 mother groups participated in the collection of pregnancy outcomes and mortality data. Of the 273 deaths among WRA, the leading causes of death reported were chronic diseases (94, 34.4%) poisoning, snake bites, and suicide (grouped together; 55, 20.1%), and accidents (29, 10.6%), while maternal mortality accounted for 7%. Nevertheless, the calculated maternal mortality ratio was quite high (259.3 per 100,000 live births).

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