Journal of Clinical Epidemiology
Volume 63, Issue 1 , Pages 9-10 , January 2010

Different measures of treatment effect for different research questions

  • Peter C. Austin

      Affiliations

    • Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
    • Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
    • Department of Health Policy, Management and Evaluation, University of Toronto, Canada
    • Corresponding Author InformationCorresponding author. Institute for Clinical Evaluative Sciences, G1 06, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada. Tel.: +1-416-480-6131; fax: +1-416-480-6048.

References 

  1. Austin PC. Absolute risk reductions, relative risks, relative risk reductions, and numbers needed to treat can be obtained from a logistic regression model. J Clin Epidemiol. 2010;63:2–7
  2. Austin PC. Absolute risk reductions and numbers needed to treat can be obtained from adjusted survival models for time-to-event outcomes. J Clin Epidemiol. 2010;63:47–56
  3. Bender R, Blettner M. Calculating the “number needed to be exposed” with adjustment for confounding variables in epidemiological studies. J Clin Epidemiol. 2002;55:525–530
  4. Bender R, Kuss O. Confidence intervals for adjusted NNEs: s simulation study. J Clin Epidemiol. 2003;56:205–206[Letter]
  5. Bender R, Kuss O, Hildebrandt M, Gehrmann U. Estimating adjusted NNT measures in logistic regression analysis. Stat Med. 2007;26:5586–5595
  6. Imbens GW. Nonparametric estimation of average treatment effects under exogeneity: a review. Rev Econ Stat. 2004;86:4–29
  7. Korevaar JC, Feith GW, Dekker FW, van Manen JG, Boeschoten EW, Bossuyt PM, et al. NECOSAD Study Group Effect of starting with hemodialysis compared with peritoneal dialysis in patients new on dialysis treatment: a randomized controlled trial. Kidney Int. 2003;64:2222–2228

PII: S0895-4356(09)00213-3

doi: 10.1016/j.jclinepi.2009.07.006

Journal of Clinical Epidemiology
Volume 63, Issue 1 , Pages 9-10 , January 2010

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