A Graphical Method for Assessing Risk Factor Threshold Values Using the Generalized Additive Model

The Multi-Ethnic Study of Atherosclerosis

Claude Messan Setodji, Maren T. Scheuner, James S. Pankow, Roger S. Blumenthal, Haiying Chen, Emmett B. Keeler

ResearchPosted on rand.org Mar 1, 2012Published in: Health Services and Outcomes Research Methodology, v. 12, no. 1, Mar. 2012, p. 62-79

Continuous variable dichotomization is a popular technique used in the estimation of the effect of risk factors on health outcomes in multivariate regression settings. Researchers follow this practice in order to simplify data analysis, which it unquestionably does. However thresholds used to dichotomize those variables are usually ad-hoc, based on expert opinions, or mean, median or quantile splits and can add bias to the effect of the risk factors on specific outcomes and underestimate such effect. In this paper, we suggest the use of a semi-parametric method and visualization for improvement of the threshold selection in variable dichotomization while accounting for mixture distributions in the outcome of interest and adjusting for covariates. For clinicians, these empirically based thresholds of risk factors, if they exist, could be informative in terms of the highest or lowest point of a risk factor beyond which no additional impact on the outcome should be expected.

Topics

Document Details

  • Availability: Non-RAND
  • Year: 2012
  • Pages: 18
  • Document Number: EP-201200-75

This publication is part of the RAND external publication series. Many RAND studies are published in peer-reviewed scholarly journals, as chapters in commercial books, or as documents published by other organizations.

RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.