The era of “Big Data” brings the hope that flexible statistical models applied to large organizational data sets yield better results and insights than those provided by traditional statistical methods. Ideally, data should be relatively free from error, and provide accurate indicators of the variables of interest. For psychological measures, this is often achieved by ascribing to established psychometric principles for measure development and evaluation, but more generally, this is also influenced by the quality and uniformity with which data are gathered, maintained, and documented.

Analytics or predictive models for “Big Data” address large samples, yet go well beyond traditional meta-analysis or large sample statistical analysis: These predictive models operate in the context of the “Vs” of Big Data (volume, velocity, variety, veracity, value), where the ...

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