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A revised SAS macro for maximum likelihood estimation of prevalence ratios using the COPY method
  1. M R Petersen1,
  2. J A Deddens1,2
  1. 1
    National Institute for Occupational Safety and Health, Cincinnati, Ohio, USA
  2. 2
    Department of Mathematical Sciences, University of Cincinnati, Cincinnati, Ohio, USA
  1. Correspondence to Martin R Petersen, National Institute for Occupational Safety and Health, Mail Stop R15, 4676 Columbia Parkway, Cincinnati, OH 45226, USA; mrp1{at}one.net

http://dx.doi.org/10.1136/oem.2008.043018

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    In a recent article (Approaches for estimating prevalence ratios. Occup Environ Med 2008;65:501–6) in the Education series of this Journal, Deddens and Petersen discuss several methods for modelling and estimating prevalence ratios. When the underlying distribution of the dependent variable is binomial, and the log of the binomial probability is related to a set of independent variables in a linear manner, approximate maximum likelihood estimates (MLEs) of the model parameters and prevalence ratios can be obtained with one of the methods, namely the COPY method.

    In 2003, Deddens et al supplied a macro for performing the COPY method calculations.1 They also provided a SAS macro for obtaining the exact MLEs for the simple case in which the model contained a single one degree of freedom independent variable. In addition they provided a theorem for any number of independent variables, provided there was only one point where the MLE of the probability of …

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    Footnotes

    • Funding This project was completed as part of the official duties of the authors as employees of the United States government.

    • Competing interests None.

    • Ethics approval The study was approved by the NIOSH Human Subjects Review Board in Cincinnati, Ohio, USA.

    • Disclaimer The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.

    • Provenance and peer review Not commissioned; externally peer reviewed.