Releases: sahirbhatnagar/casebase
casebase v0.10.5
- Skip tests when R is compiled against ATLAS BLAS
- Set seed for reproducible tests
- Addressed deprecation warning in ggplot2
v0.10.1
What's Changed
- Removed
family = "gbm"
as it wasn't properly tested. - Added
confint.singleEventCB
to compute confidence bands for the risk (or survival) function. - Updated
ERSPC
data so that the exposure variable is categorical. This may break previous code explicitly making this conversion, or somehow relying on the numerical coding. - fix issue 143 by @turgeonmaxime in #144
- Issue 149 by @turgeonmaxime in #150
- Issue 151 by @turgeonmaxime in #152
Full Changelog: v0.9.1...v0.10.1
casebase 0.9.1
- Fixed issue with
plot.singleEventCB()
whenvisreg
package is not loaded. - Improved error message when using
family = "glmnet"
with a single covariate. - Introduced
summary
method for objects of classsingleEventCB
, and improved the output ofprint
by displaying the appropriate function call.
casebase 0.9.0
This is a Major new release
Breaking changes
- The output of
absoluteRisk()
now always contains the time variable in the first column, regardless of the length oftime
. This will break earlier code that depended on the previous behaviour. - Population time plots now use
ggplot2::geom_ribbon()
instead ofggplot2::geom_segment()
. - Population time functions now allow for more flexible plots with user defined arguments including sequentially adding base, case, and competing event series. These are now passed as a list to the
*.params
arguments. Several arguments are now deprecated. - Removed
popTimeExposure
class and the correspondingplot
method.popTime()
now returns anexposure
attribute which contains the name of the exposure variable in the dataset. The plot method for objects of classpopTime
will use this exposure attribute to create exposure stratified population time plots.
New features
- Major refactoring of
absoluteRisk()
. Trapezoidal rule to perform numerical integration for absolute risk estimation, providing significant speed up. - Users now have further control on the output of
absoluteRisk()
using the argumentstype
andaddZero
. - New plotting method for time-dependent hazard functions and hazard ratios. These include confidence intervals. See
plot.singleEventCB()
. The hazard function plot requires thevisreg
package to be installed. - New plotting method for cumulative incidence and survival curves. See
plot.absRiskCB()
. - When
time
is unspecified,absoluteRisk()
now computes the cumulative incidence atntimes
equidistant points between 0 and the max failure time. absoluteRisk()
can now compute the cumulative incidence for a"typical"
covariate profile withnewdata = "typical"
. "Typical" corresponds to the median for continuous variables and the mode for factors (each variable is summarised independently).- Added
eprchd
,brcancer
,support
andsimdat
datasets to the package. - Implemented
riskRegression::predictRisk()
method forsingleEventCB
objects.
Minor improvements and fixes
- No longer importing the entire namespace of
data.table
andggplot2
. - Moved from make the docs to pkgdown for package website.
- A warning is given when
family="gbm"
and nonlinear functions of time or interactions are specified. - Add
singleEventCB
class to object returned byfitSmoothHazard()
- Add
absRiskCB
class to object returned byabsoluteRisk()
- Use
glmnet::prepareX
to convert factors into indicator variables
Initial release on CRAN
This is the first release of the casebase
package on CRAN which implements the case-base sampling approach of Hanley and Miettinen (2009), Saarela and Arjas (2015), and Saarela (2015), for fitting flexible hazard regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression. From the fitted hazard function, cumulative incidence, risk functions of time, treatment and profile can be derived. This approach accommodates any log-linear hazard function of prognostic time, treatment, and covariates, and readily allows for non-proportionality. We also provide a plot method for visualizing incidence density via population time plots. Comprehensive documentation is available at http://sahirbhatnagar.com/casebase/