A Bayesian Approach to Measurement Bias in Networking Studies

Ling Zhu, Scott E. Robinson, René Torenvlied

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)

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
Original languageEnglish
Pages (from-to)-
JournalAmerican review of public administration
DOIs
Publication statusPublished - 17 Mar 2014

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networking
trend
manager
open system
model theory
Bayesian approach
Measurement bias
Networking
mail survey
public administration
credit
Managers
performance
Factors

Keywords

  • METIS-303631
  • IR-91079

Cite this

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A Bayesian Approach to Measurement Bias in Networking Studies. / Zhu, Ling; Robinson, Scott E.; Torenvlied, René.

In: American review of public administration, 17.03.2014, p. -.

Research output: Contribution to journalArticleAcademicpeer-review

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