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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 of msm 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 use survplot() 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" ).

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install.packages('msmtools')

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Version

1.2

License

GPL-3

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Last Published

June 21st, 2016

Functions in msmtools (1.2)