Estimates disease prevalence for a given index date, using existing registry data extended with Monte Carlo simulations.
rprev estimates disease prevalence at a specified index date from registry data. To improve the estimate accuracy, Monte Carlo simulation techniques are used to simulate incident cases in years for which incidence data is unavailable. Disease survival is modelled with parametric Weibull regression. See the user_guide vignette for more details about the implementation, and the original publication for details of the algorithm, available at http://www.ncbi.nlm.nih.gov/pubmed/24656754.
To install from CRAN, simply use
install.packages('rprev'). The code is currently not available elsewhere.
The posterior age distribution, returned from
prevalence as in the
simulated object, is now stored in the format of a nested list rather than a matrix as before. The first dimension of the list corresponds to each sex (if applicable), the next indexing the number of years of simulated cases, and the final corresponds to the bootstrap samples. The final level comprises a vector holding the ages of the simulated cases which are still contributing to prevalence at the index date from the corresponding sex, year, and bootstrap sample number.
Minor bug fixes and a slight change to the parameterisation of prevalence:
First release of the package, working with all features necessary to provide estimates of point prevalence. Issues which we'd like to address in future releases are: