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Interpreting and Visualizing Regression Models Using Stata

Author

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  • Michael N. Mitchell

Abstract

Michael Mitchell’s Interpreting and Visualizing Regression Models Using Stata is a clear treatment of how to carefully present results from model-fitting in a wide variety of settings. It is a boon to anyone who has to present the tangible meaning of a complex model in a clear fashion, regardless of the audience. As an example, many experienced researchers start to squirm when asked to give a simple explanation of the practical meaning of interactions in nonlinear models such as logistic regression. The techniques presented in Mitchell's book make answering those questions easy. The overarching theme of the book is that graphs make interpreting even the most complicated models containing interaction terms, categorical variables, and other intricacies straightforward.

Suggested Citation

  • Michael N. Mitchell, 2012. "Interpreting and Visualizing Regression Models Using Stata," Stata Press books, StataCorp LP, number ivrm, December.
    • Handle: RePEc:tsj:spbook:ivrm
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    File URL: http://stata-press.com/books/interpreting-visualizing-regression-models/
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    File URL: http://stata-press.com/books/ivrm-preface.pdf
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    Citations

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    Cited by:

    1. Stoetzer Matthias-Wolfgang & Ernst Daniel, 2015. "Arbeitsplatzeffekte von Innovationen auf Unternehmensebene: Eine Meta-Analyse der empirischen Evidenz," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 16(2), pages 173-188, June.
    2. Bornmann, Lutz & Williams, Richard, 2013. "How to calculate the practical significance of citation impact differences? An empirical example from evaluative institutional bibliometrics using adjusted predictions and marginal effects," Journal of Informetrics, Elsevier, vol. 7(2), pages 562-574.
    3. repec:kap:sbusec:v:50:y:2018:i:1:d:10.1007_s11187-017-9884-4 is not listed on IDEAS
    4. Lam, Marcus & Klein, Sacha & Freisthler, Bridget & Weiss, Robert E., 2013. "Child center closures: Does nonprofit status provide a comparative advantage?," Children and Youth Services Review, Elsevier, vol. 35(3), pages 525-534.
    5. Jeremiah Bohr, 2014. "Public views on the dangers and importance of climate change: predicting climate change beliefs in the United States through income moderated by party identification," Climatic Change, Springer, vol. 126(1), pages 217-227, September.
    6. Ronald Mincy & Hillard Pouncy & Afshin Zilanawala, 2016. "Race, Romance and Nonresident Father Involvement Resilience: Differences by types of involvement," Working Papers wp16-05-ff, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Research on Child Wellbeing..

    More about this item

    Keywords

    Stata; regression; marginal effects; predictions;

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