Visualizing effect modification on contrasts

Niels Henrik Bruun

Stata Journal, 2019, vol. 19, issue 3, 566-580

Abstract: A recurring problem in statistics is estimating and visualizing nonlinear dependency between an effect and an effect modifier. One approach to handle this is polynomial regressions of some order. However, polynomials are known for fitting well only in limited ranges. In this article, I present a simple approach for estimating the effect as a contrast at selected values of the effect modifier. I implement this approach using the flexible restricted cubic splines for the point estimation in a new simple command, emc. I compare the approach with other classical approaches addressing the problem.

Keywords: emc; effect modification (search for similar items in EconPapers)
Date: 2019
Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj19-3/st0567/
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.stata-journal.com/article.html?article=st0567 link to article purchase

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tsj:stataj:v:19:y:2019:i:3:p:566-580

Ordering information: This journal article can be ordered from
http://www.stata-journal.com/subscription.html

DOI: 10.1177/1536867X19874226

Access Statistics for this article

Stata Journal is currently edited by Nicholas J. Cox and Stephen P. Jenkins

More articles in Stata Journal from StataCorp LLC
Bibliographic data for series maintained by Christopher F. Baum () and Lisa Gilmore ().