Building augmented data for multi-state models: the msmtools
package
msmtools
introduces a fast and general method for restructuring classical longitudinal datasets
into augmented ones. The reason for this is to facilitate the modeling of longitudinal data
under a multi-state framework using the msm
package.
msmtools
comes with 3 functions:
augment()
: the main function of the package. This is the workhorse which takes care of the
data reshaping. It is very efficient and fast so highly dimensional datasets can be processed with ease;
prevplot()
: this is a plotting function which mimics the usage ofmsm
function
plot.prevalence.msm()
, but with more things. Once you ran a multi-state model, use this function
to plot a comparison between observed and expected prevalences;
survplot()
: the aims of this function are double. You can usesurvplot()
as a plotting tool
for comparing the empirical and the fitted survival curves. Or you can use it to build and get
the datasets used for the plot. The function is based on msm
plot.survfit.msm()
, but does
more things and it is a lot faster.
For more information about msmtools
, please check out the vignette with
vignette( "msmtools" )
.