0000000001311748
AUTHOR
John Antonakis
Rejoinder: fractures in the edifice of PLS
Purpose This study aims to provide a response to the commentary by Yuan on the paper “Marketing or Methodology” in this issue of EJM. Design/methodology/approach Conceptual argument and statistical discussion. Findings The authors find that some of Yuan’s arguments are incorrect, or unclear. Further, rather than contradicting the authors’ conclusions, the material provided by Yuan in his commentary actually provides additional reasons to avoid partial least squares (PLS) in marketing research. As such, Yuan’s commentary is best understood as additional evidence speaking against the use of PLS in real-world research. Research limitations/implications This rejoinder, coupled with Yuan’s comm…
On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Entities such as individuals, teams, or organizations can vary systematically from one another. Researchers typically model such data using multilevel models, assuming that the random effects are uncorrelated with the regressors. Violating this testable assumption, which is often ignored, creates an endogeneity problem thus preventing causal interpretations. Focusing on two-level models, we explain how researchers can avoid this problem by including cluster means of the Level 1 explanatory variables as controls; we explain this point conceptually and with a large-scale simulation. We further show why the common practice of centering the predictor variables is mostly unnecessary. Moreover, …
Supplemental Material, Coloring_and_code_issues_appen - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Supplemental Material, Coloring_and_code_issues_appen for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods
Supplemental Material, sj-docx-1-orm-10.1177_1094428119877457 - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Supplemental Material, sj-docx-1-orm-10.1177_1094428119877457 for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods
Supplemental Material, Coding_book - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Supplemental Material, Coding_book for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods
Marketing or methodology? : Exposing the fallacies of PLS with simple demonstrations
Purpose Over the past 20 years, partial least squares (PLS) has become a popular method in marketing research. At the same time, several methodological studies have demonstrated problems with the technique but have had little impact on its use in marketing research practice. This study aims to present some of these criticisms in a reader-friendly way for non-methodologists. Design/methodology/approach Key critiques of PLS are summarized and demonstrated using existing data sets in easily replicated ways. Recommendations are made for assessing whether PLS is a useful method for a given research problem. Findings PLS is fundamentally just a way of constructing scale scores for regression. PL…
Supplemental Material, sj-rar-1-orm-10.1177_1094428119877457 - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Supplemental Material, sj-rar-1-orm-10.1177_1094428119877457 for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods
Supplemental Material, Coded_data_in_Excel_compressed_to_put_on_line - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Supplemental Material, Coded_data_in_Excel_compressed_to_put_on_line for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods
Supplemental Material, sj-dta-1-orm-10.1177_1094428119877457 - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Supplemental Material, sj-dta-1-orm-10.1177_1094428119877457 for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods
Supplemental Material, Coded_data_in_Stata_to_put_on_line - On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations
Supplemental Material, Coded_data_in_Stata_to_put_on_line for On Ignoring the Random Effects Assumption in Multilevel Models: Review, Critique, and Recommendations by John Antonakis, Nicolas Bastardoz and Mikko Rönkkö in Organizational Research Methods