Assessing the sensitivity of decision-analytic results to unobserved markers of risk: defining the effects of heterogeneity bias.

@article{Kuntz2002AssessingTS,
  title={Assessing the sensitivity of decision-analytic results to unobserved markers of risk: defining the effects of heterogeneity bias.},
  author={Karen M. Kuntz and Sue J. Goldie},
  journal={Medical decision making : an international journal of the Society for Medical Decision Making},
  year={2002},
  volume={22 3},
  pages={218-27}
}
An important assumption made when constructing a Markov model is that all persons residing in a health state are identical. Failure to adjust for population heterogeneity caused by unobserved variables can therefore cause bias in model results. The authors used a simple model to evaluate the potential impact of heterogeneity bias, defined as the percentage change in the life expectancy gain with an intervention predicted by a model that does not adjust for heterogeneity (unadjusted model… CONTINUE READING

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