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The cross-product ratio in bivariate lognormal and gamma distributions, with an application to non-randomized trials

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  • Paul Baxter
  • Paul Marchant

Abstract

Non-randomized trials can give a biased impression of the effectiveness of any intervention. We consider trials in which incidence rates are compared in two areas over two periods. Typically, one area receives an intervention, whereas the other does not. We outline and illustrate a method to estimate the bias in such trials under two different bivariate models. The illustrations use data in which no particular intervention is operating. The purpose is to illustrate the size of the bias that could be observed purely due to regression towards the mean (RTM). The illustrations show that the bias can be appreciably different from zero, and even when centred on zero, the variance of the bias can be large. We conclude that the results of non-randomized trials should be treated with caution, as interventions which show small effects could be explained as artefacts of RTM.

Suggested Citation

  • Paul Baxter & Paul Marchant, 2010. "The cross-product ratio in bivariate lognormal and gamma distributions, with an application to non-randomized trials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(4), pages 529-536.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:4:p:529-536
    DOI: 10.1080/02664760902744962
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