Stata Tip 87: Interpretation of Interactions in Nonlinear Models

By M. Buis. 2010

476 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4a5ea076724d1c9a907991875168f3ea89111a83

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Citations in the corpus

Do (Fe)Male Auditors Impair Audit Quality? Evidence from Going-Concern Opinions (2016, background): “An interpretation that is useful in this study is that an interaction between SEX and another variable Y tells us by how much the effect of Y differs between female and male auditors in multiplicative terms (Buis, 2010).”
Birth Order Effects on Educational Attainment and Educational Transitions in West Germany (2014, unknown): “of making the respective transition (Buis, 2010).”
The U.S. left behind? Financial globalization and the rise of IPOs outside the U.S. (2013, methodology): “We first use a Chow (1960) structural break test in which we allow the coefficients in the panel regression model to shift around a pre-specified breakpoint year.”
Is Kindergarten the New First Grade? (2016, methodology): “It is important to note that our approach to examining interactions is based on the odds ratio metric and that had we used a probability metric, the interaction terms of interest may suggest different patterns (Buis, 2010).”
Cultural Differences and Geography as Determinants of Online Prosocial Lending (2014, methodology): “(Allison and Waterman 2002; Buis 2010; Ghose et al. 2013)”
Dif-in-Dif Estimators of Multiplicative Treatment Effects (2014, unknown): “This point is related 6Similarly, Buis (2010) pointed out that in an exponential model the interaction term should be interpreted in a multiplicative scale.”
Financial constraints and public funding of eco-innovation: empirical evidence from European SMEs (2018, background): “…12 and focusing on the first two rows, we can think of the marginal effect of the lack of public funding when the firm has no lack of external financing as the difference between the expected odds of firms with and without lack of public funding when LACK_EXT_FIN is equal to zero (Buis, 2010).”
Using Predictions and Marginal Effects to Compare Groups in Regression Models for Binary Outcomes (2018, background): “…attracted considerable attention across many disciplines, both directly in research dealing with statistical methods for comparing groups and indirectly in research about interactions in nonlinear models (e.g., Ai and Norton 2003; Buis 2010; Kendler and Gardner 2010; Norton, Wang, and Ai 2004).”