# One-Tailed or Two-Tailed P Values in PLS-SEM?

Ned Kock (Division of International Business and Technology Studies, Texas A&M International University, Laredo, TX, USA)
DOI: 10.4018/ijec.2015040101
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## Abstract

Should P values associated with path coefficients, as well as with other coefficients such as weights and loadings, be one-tailed or two-tailed? This question is answered in the context of structural equation modeling employing the Partial Least Squares Method (PLS-SEM), based on an illustrative model of the effect of e-collaboration technology use on job performance. A one-tailed test is recommended if the coefficient is assumed to have a sign (positive or negative), which should be reflected in the hypothesis that refers to the corresponding association. If no assumptions are made about coefficient sign, a two-tailed test is recommended. These recommendations apply to many other statistical methods that employ P values, including path analyses in general, with or without latent variables, plus univariate and multivariate regression analyses.
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## Illustrative Model

The discussion presented in this study is based on the illustrative model shown in Figure 1. This model contains two latent variables, e-collaboration technology use (L) and job performance (J). Each latent variable is measured indirectly through three indicators.

Figure 1.

Illustrative model

Let us assume that , , and () are scaled to have a mean of zero and a standard deviation of one (i.e., these variables are standardized). Our illustrative model can then be described by equations (1), (2), and (3).

,
. (1)
,
. (2)
. (3)

The path coefficient and loadings and () are assumed to describe the model at the population level, as true values. The population is made of teams of individuals who use an integrated e-collaboration technology including e-mail and voice conferencing to different degrees. That is, the unit of analysis is the team, not the individual.

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