An approach for quantifying small effects in regression models

Edward J. Bedrick, Lauren Hund

Research output: Contribution to journalArticlepeer-review

Abstract

We develop a novel approach for quantifying small effects in regression models. Our method is based on variation in the mean function, in contrast to methods that focus on regression coefficients. Our idea applies in diverse settings such as testing for a negligible trend and quantifying differences in regression functions across strata. Straightforward Bayesian methods are proposed for inference. Four examples are used to illustrate the ideas.

Original languageEnglish (US)
Pages (from-to)1088-1098
Number of pages11
JournalStatistical Methods in Medical Research
Volume27
Issue number4
DOIs
StatePublished - Apr 1 2018

Keywords

  • Analysis of covariance
  • interaction
  • negligible effects
  • R-squared
  • tests for equivalence

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

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