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.
ggsurvfit to v1.2.0 to
address updates made in ggplot2 v4.0.0.if(FALSE){}. In
write_to_xl.Rd, we now use \dontrun{} to prevent an Excel
file from being created, saved and launched.fit_models() documentation.fs package.
fs::path_package() was replaced with
system.file().roxygen2 documentation to support auto-linking to external
documentation.tidymodels framework for survival
analysis. Several updates were required to reflect this change including
to function names, arguments, supporting documentation, and templates.
tidymodels framework is a collection of R packages
for modeling and machine learning using tidyverse
principles. From the tidymodels framework, we take
advantage of the parsnip and censored packages
to specify models and predict survival outputs.parsnip package provides an interface to many
different modeling packages, allowing for a consistent syntax for
fitting models and making predictions.censored package is a parsnip
extension that provides engines for various models to handle censored
data in survival analysis.inspect_surv_data() allows quick inspection of survival
data.get_km() replaces quick_KM() as the
function to fit Kaplan-Meier curves.test_ph() replaces quick_PH() as the
function to test the proportional hazards assumption.fit_models() allows for additional covariates to be
specified in model fitting.predict_and_plot() separates the generation of
predictions and associated plots from the main model fitting
function.cli package for key
functions to simplify and summarise outputs.ggsurvplot to
ggsurvfit. ggsurvplot generates warning
messages when median survival lines are added and generates misaligned
risk tables as of ggplot2 version 3.5.0, while
ggsurvfit is being actively maintained.plot() run on the output of fit_models()
acts as a call to predict_and_plot(), generating
predictions and plots for the specified model.plot_fits() now uses flexsurv to generate survival
predictions in plots, which matches the prediction method in
predict_fits(). The original prediction method (via survHE)
can be used instead by setting the new argument
plot_predictions = "survHE" for plot_fits()
and any functions that use plot_fits() (e.g.,
quick_fit_select(), quick_fit()).predict_fits() now outputs a list object that includes
95% confidence intervals for the predicted survival probabilities. CIs
can be excluded by setting include_ci = FALSE. The
include_ci argument is available for all functions that use
predict_fits() or objects generated by
predict_fits() (e.g., quick_fit_select(),
quick_fit()).cli package has been added to
support aesthetic and informative warning messages, such as in the
quick_to_XL() function.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.