20 research outputs found

    Size does matter: How varying group sizes in a sample affect the most common measures of group diversity

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    Work group diversity can be conceptualized in different ways (i.e., variety, separation, and disparity), and the appropriate operationalization of a diversity dimension depends on which of these diversity types researchers have in mind. Based on prior work on the measurement of the different types of diversity, we show that the most common diversity indexes (i.e., Blau’s index, Teachman’s index, standard deviation, mean Euclidean distance [MED], Gini coefficient, and coefficient of variation) are systematically biased whenever they are used in field studies in which the overall sample comprises groups of varying sizes. Using simulated data, we illustrate this bias inherent in all of the common diversity measures. This bias can lead to erroneous conclusions concerning the impact of group size and the relationship between group diversity and group outcomes. We offer bias-corrected formulas and suggest that diversity researchers henceforth use these adjusted versions when investigating the effects of group diversity in organizational settings
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