Abstract
As a field, we should put more emphasis on interpreting the magnitude of coefficient estimates rather than only assessing statistical significance. To support this claim, I demonstrate how focusing only on statistical significance can lead to incorrect and incomplete conclusions in many common applications of the linear regression model. Moreover, I demonstrate why interpreting coefficient estimates in common non-linear estimators (e.g., probit, logit, Poisson, and negative binomial estimators) requires additional care compared to the linear regression model.
Original language | English (US) |
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Title of host publication | Research Methodology in Strategy and Management |
Editors | David Ketchen, Donald Bergh |
Pages | 273-293 |
Number of pages | 21 |
DOIs | |
State | Published - 2007 |
Publication series
Name | Research Methodology in Strategy and Management |
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Volume | 4 |
ISSN (Print) | 1479-8387 |
Bibliographical note
Copyright:Copyright 2008 Elsevier B.V., All rights reserved.