Are We Drawing the Correct Conclusions? Regression Analysis in the Nonprofit Literature


  • Robert Shearer Pepperdine University
  • Truman Clark Pepperdine University



Regression analysis, Multicollinearity, Statistical significance / Analyse de régression, Multicolinéarité, Signification statistique


Linear models are the most commonly used analytical tools in the nonprofit literature. Academics and practitioners utilize these models to test different hypotheses in support of their research efforts, seeking to find significant results that substantiate their theories. And yet the authors of this article have discovered a surprisingly large number of insignificant results in articles from established nonprofit journals. Insignificant hypotheses and Type II errors surely account for a number of these results, but the authors believe the majority of these results are due to a different cause, one that is detectable and preventable: multicollinearity.

Dans les articles sur les organismes sans but lucratif, les modèles linéaires sont les outils analytiques les plus communément utilisés. En effet, académiques et praticiens utilisent tous les deux ces modèles pour évaluer diverses hypothèses relatives à leurs recherches, espérant trouver des résultats significatifs pouvant confirmer leurs théories. Pourtant, les auteurs de cet article ont découvert un nombre surprenant de résultats non significatifs dans des articles de revues établies sur les organismes sans but lucratif. Des hypothèses non significatives et des erreurs du type II expliquent sûrement certains de ces résultats, mais les auteurs croient que la majorité des résultats ont une cause différente qui est détectable et évitable : la multicolinéarité.


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Author Biographies

Robert Shearer, Pepperdine University

Assistant Professor of Decision Science

Business Administration Division

Truman Clark, Pepperdine University

Business Administration Division


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