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

@article{Kock2018MinimumSS,
  title={Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods},
  author={Ned Kock and Pierre Hadaya},
  journal={Information Systems Journal},
  year={2018},
  volume={28},
  pages={227 - 261}
}
  • N. KockP. Hadaya
  • Published 1 January 2018
  • Mathematics
  • Information Systems Journal
Partial 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. [] Key Method 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…

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