Background
Probabilistic sensitivity analysis (PSA) in cost-effectiveness analysis involves sampling a large number of
realisations of an economic model. For some parameters, we may be uncertain around the true mean values of
the variables, but the ordering of the values is known. Typical sampling approaches lack either statistical or
clinical validity. For example, sampling using a common number generator results in extreme dependence and
independent sampling can lead to realisations with incorrect ordering.
Methods
We propose a new sampling approach for ordered parameters, the Difference Method approach, which samples
the parameters of interest via a difference parameter. If the parameters of interest are bounded, it involves
transforming the variables so that they are unbounded and then sampling via the difference parameter. We have
provided an Excel workbook to implement the method. The proposed approach is illustrated with an example
sampling ordered parameters for utility and cost.
Results
The DM approach has a number of advantages when comparing with the typical approaches used in practice.
The DM approach generates PSA samples which have similar summary statistics as the given values in our
examples whilst maintaining the constraint that one value was greater than another. The method also implies
plausible positive correlation between the two ordered variables.
Conclusions
Both clinical and statistical validity should be checked when producing PSA samples. The DM approach should
be considered as a solution to potential problems in generating PSA samples for ordered parameters.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)