Revisiting Bias Due to Construct Misspecification: Different Results from Considering Coefficients in Standardized Form

• Published in: MIS quarterly 2012-03, Vol.36 (1), p.123-138
• Main Authors: Aguirre-Urreta, Miguel I., Marakas, George M.
• Format: Article
• Language: English
• Subjects: Bias; Estimation bias; False negative errors; Information storage and retrieval systems; Information systems; Modeling; Parametric models; Population estimates; Research biases; Research design; Research Notes; Simulation; Standardized tests; Statistical discrepancies; Statistical variance; Studies
• ISSN: 0276-7783; 2162-9730
• DOI: 10.2307/41410409

Researchers in a number of disciplines, including Information Systems, have argued that much of past research may have incorrectly specified the relationship between latent variables and indicators as reflective when an understanding of a construct and its measures indicates that a formative specification would have been warranted. Coupled with the posited severe biasing effects of construct misspecification on structural parameters, these two assertions would lead to concluding that an important portion of our literature is largely invalid. While we do not delve into the issue of when one specification should be employed over another, our work here contends that construct misspecification, but with a particular exception, does not lead to severely biased estimates. We argue, and show through extensive simulations, that a lack of attention to the metric in which relationships are expressed is responsible for the current belief in the negative effects of misspecification.