A Bayesian Approach to Measurement Bias in Networking Studies. (September 2015)

• Record Type: Journal Article
• Authors: Zhu, Ling; Robinson, Scott E.; Torenvlied, René
• Is Part Of: American review of public administration. Volume 45:Number 5(2015:Sep.)
• Page Start: 542
• Page End: 564
• Publication Date: 2015-09
• Subjects: managerial networking -- measurement bias -- Bayesian IRT; Public administration -- Periodicals; Public administration -- United States -- Periodicals; 351
• DOI: 10.1177/0275074014524299
• Languages: English
• ISSNs: 0275-0740

Abstract

The study of managerial networking has been growing in the field of public administration; a field that analyzes how managers in open system organizations interact with different external actors and organizations. Coincident with this interest in managerial networking is the use of self-reported survey data to measure managerial behavior in building and maintaining networks. One predominant approach is to generate factor indices of networking activity from ordinal scales. However, when public managers answer survey questions with ordinal scales to describe their networking activities, the answers may be subject to various response biases. Consequently, the use of factor indices may lead to biased measurements that misrepresent managerial networking. As an alternative, we build on studies that apply the item response theory (IRT) as a measurement strategy and propose a Bayesian alternative. To tap managers' latent effort put in networking activity, the Bayesian Generalized Partial Credit Model allows us to select a one-dimensional networking scale from multiple ordinal survey items. Using 12 such items in a mail survey of nearly 1, 000 American hospital managers, we demonstrate the advantage of using the Bayesian IRT model over factor-analytic models in a substantive test of how managerial networking affects organizational performance.