Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods

Information Systems Journal - Tập 28 Số 1 - Trang 227-261 - 2018
Ned Kock1, Pierre Hadaya2
1Division of International Business and Technology Studies Texas A&M International University 5201 University Boulevard Laredo TX 78041 USA
2Department of Management and Technology École des Sciences de la Gestion, Université du Québec à Montréal PO Box 8888, Downtown Station Montreal Quebec H3C 3P8 Canada

Tóm tắt

AbstractPartial least squares‐based structural equation modelling (PLS‐SEM) is extensively used in the field of information systems, as well as in many other fields where multivariate statistical methods are used. One of the most fundamental issues in PLS‐SEM is that of minimum sample size estimation. The ‘10‐times rule’ has been a favourite because of its simplicity of application, even though it tends to yield imprecise estimates. We propose two related methods, based on mathematical equations, as alternatives for minimum sample size estimation in PLS‐SEM: the inverse square root method, and the gamma‐exponential method. Based on three Monte Carlo experiments, we demonstrate that both methods are fairly accurate. The inverse square root method is particularly attractive in terms of its simplicity of application. © 2016 John Wiley & Sons Ltd

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Information Systems Journal

Tập 28 Số 1

227-261

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