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Estimation of Transition Probabilities in Multistate Models.
The TPmsm software contains functions that compute estimates for the transition probabilities in the illness-death model and or the three-state progressive model. This R package implements seven different estimators. Being five of them non-parametric and two of them semi-parametric (PAJ and KMPW). The implemented estimators are the Aalen-Johansen estimator (AJ), Presmoothed Aalen-Johansen estimator (PAJ), Kaplan-Meier Weighted estimator (KMW), Presmoothed Kalpan-Meier Weighted estimator (KMPW), Inverse Probability Censoring estimator (IPCW), Lin estimator (LIN) and Location-Scale estimator (LS). The Inverse Probability Censoring (IPCW) and Lin (LIN) estimators also permit to compute transition probabilities conditioned on a single covariate. Bootstrap confidence bands can be computed for each of the mentioned estimators. Several graphical plots of the transition probabilities with or without confidence bands can be drawn. To aid in the study of the statistical properties of the implemented estimators, functions to generate pseudo-random data for some well-known multivariate distributions were implemented.
If you want to use the release version of the TPmsm package, you can install the package from CRAN as follows:
If you want to use the development version of the TPmsm package, you can install the package from GitHub via the remotes package:
remotes::install_github(
repo="arturstat/TPmsm",
build=TRUE,
build_opts="--compact-vignettes=gs+qpdf",
build_manual=TRUE,
build_vignettes=TRUE,
);Artur Araújo, Javier Roca-Pardiñas roca@uvigo.es
and Luís Meira-Machado lmachado@math.uminho.pt
Maintainer: Artur Araújo artur.stat@gmail.com
This research was financed by FEDER Funds through Programa Operacional Factores de Competitividade – COMPETE and by Portuguese Funds through FCT – Fundação para a Ciência e a Tecnologia, in the form of grants PTDC/MAT/104879/2008 and PEst-OE/MAT/UI0013/2014.
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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.