Sample size determination and statistical power analysis in PLS using R: An annotated tutorial
Article
Aguirre-Urreta, M, Rönkkö, M. (2015). Sample size determination and statistical power analysis in PLS using R: An annotated tutorial
. COMMUNICATIONS OF THE ASSOCIATION FOR INFORMATION SYSTEMS, 36 33-51. 10.17705/1cais.03603
Aguirre-Urreta, M, Rönkkö, M. (2015). Sample size determination and statistical power analysis in PLS using R: An annotated tutorial
. COMMUNICATIONS OF THE ASSOCIATION FOR INFORMATION SYSTEMS, 36 33-51. 10.17705/1cais.03603
Partial least squares (PLS) is one of the most popular analytical techniques employed in the information systems field. In recent years, researchers have begun to revisit commonly used rules-of-thumb about the minimum sample sizes required to obtain reliable estimates for the parameters of interest in structural research models. Of particular importance in this regard is the a priori assessment of statistical power, which provides valuable information to be used in the design and planning of research studies. Though the importance of conducting such analyses has been recognized for quite some time, a review of the empirical research employing PLS indicates that they are not regularly conducted or reported. One likely reason is the lack of software support for these analyses in popular PLS packages. In this tutorial, we address this issue by providing, in tutorial form, the steps and code necessary to easily conduct such analyses. We also provide guidance on the reporting results.
