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The Elephant in the Room: Evaluating the Predictive Performance of Partial Least Squares (PLS) Path Models

https://doi.org/10.2139/ssrn.2659233
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17/17 checkable references clean · checked 2026-08-27

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

8 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 17 checked references that resolve
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Illusions in regression analysis
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A Paradigm for Developing Better Measures of Marketing Constructs
resolves10.3102/10769986029003317
The Superiority of Simple Alternatives to Regression for Social Science Predictions
resolves10.1016/0304-4076(83)90094-5
Some comments on maximum likelihood and partial least squares methods
resolves10.1007/978-3-540-32827-8_2
Latent Variables and Indices: Herman Wold’s Basic Design and Partial Least Squares
resolves10.1007/s11747-011-0300-3
Guidelines for choosing between multi-item and single-item scales for construct measurement: a predictive validity perspective
resolves10.1080/10705510903439003
A Comparison of Approaches for the Analysis of Interaction Effects Between Latent Variables Using Partial Least Squares Path Modeling
resolves10.1016/s0169-2070(01)00112-1
Bootstrap prediction intervals for single period regression forecasts
resolves10.1007/978-1-4614-8283-3_13
A Comparison of PLS and ML Bootstrapping Techniques in SEM: A Monte Carlo Study
resolves10.1177/0165025413515169
Using Monte Carlo simulations to determine power and sample size for planned missing designs
resolves10.1214/10-sts330
To Explain or to Predict?
resolves10.2307/23042796
Predictive Analytics in Information Systems Research1
resolves10.1016/j.csda.2004.03.005
PLS path modeling
resolves10.1007/bf02293687
Simulating Multivariate Nonnormal Distributions
resolves10.1007/978-1-4613-8171-6_14
Models for Knowledge
resolves10.1016/j.ausmj.2011.04.004
Responding to the Severe Limitations of Cross-Sectional Surveys: Commenting on Rong and Wilkinson's Perspectives
resolves10.1016/j.jbusres.2012.12.021
Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory
The 8 references without a DOI — listed, not checked
no DOI — not checkedThe Partial Least Squares (PLS) Approach to Causal Modeling, Personal Computer Adoption and Use as an Illustration
no DOI — not checkedOn partial least squares variance�based SEM (VBSEM) vs. covariance�based SEM (CBSEM) for confirmatory analysis: It's all about the components and variance explained
no DOI — not checkedref9
no DOI — not checkedComparing the Predictive Ability of PLS and Covariance Analysis
no DOI — not checkedComparing Out�of�Sample Predictive Ability of PLS, Covariance, and Regression Models
no DOI — not checkedsemPLS: structural equation modeling using partial least squares
no DOI — not checkedsimsem: SIMulated Structural Equation Modeling in R
no DOI — not checkedref17
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