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Group & Organization Management
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Silver Bullet or Voodoo Statistics?

A Primer for Using the Partial Least Squares Data Analytic Technique in Group and Organization Research

John J. Sosik

Pennsylvania State University

Surinder S. Kahai

State University of New York at Binghamton

Michael J. Piovoso

Pennsylvania State University

Much of group and organization research is constrained by either limited sample sizes and/or nascent theoretical development. Wold developed the partial least squares (PLS) data analytical technique to help overcome these and other challenges facing researchers. PLS represents a powerful and effective means to test multivariate structural models with latent variables. Although PLS is used by researchers and practitioners in many scientific disciplines, some misunderstanding remains among group and organization researchers regarding the legitimacy and usefulness of PLS. To help allay these concerns, this article provides a nontechnical primer on PLS and its advantages, limitations, and application to group and organization research using a data set collected in an experiment on the effects of leadership styles and communication format on the group potency of computer-mediated work groups.

Key Words: partial least squares • soft modeling • multivariate analysis • small samples • nascent theory testing

Group & Organization Management, Vol. 34, No. 1, 5-36 (2009)
DOI: 10.1177/1059601108329198
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