The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
We run a simulation study to verify the models in pmrm
are implemented correctly. For each simulation scenario (model type and
disease progression trajectory), we:
RTMB R code.RTMB-powered implementation.Around half of the 50% confidence intervals from (2) should cover the true data-generating parameter values in (1). Likewise, around 95% of the 95% confidence intervals from (2) should cover the truth. In addition, we expect all models to converge.
This simulation study is a targets pipeline in the
vignettes/validation/ directory of the source code of
pmrm. To run the pipeline, change to that working directory
and call targets::tar_make(). Due to the computational
cost, we only run this pipeline once per release.
The following table shows the percentage of fitted models that converged for each scenario.
read_csv(file.path("validation", "convergence.csv")) |>
mutate(convergence = label_percent()(convergence)) |>
kable()| scenario | convergence |
|---|---|
| exponential_decline_nonproportional | 100% |
| exponential_decline_proportional | 100% |
| exponential_slowing_nonproportional | 100% |
| exponential_slowing_proportional | 100% |
| linear_decline_nonproportional | 100% |
| linear_decline_proportional | 100% |
| linear_slowing_nonproportional | 100% |
| linear_slowing_proportional | 100% |
The following plot shows the percentage of confidence intervals that covered the true parameter values. Coverage is shown separately for each parameter in each scenario. For reference, the expected coverage rate is shown as a horizontal solid in each facet.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.