R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
calibmsm
Calibration Plots for the Transition Probabilities from Multistate Models
View on CRAN: Click
here
Download and install calibmsm package within the R console
Install from CRAN:
install.packages("calibmsm")
Install from Github:
library("remotes")
install_github("cran/calibmsm") Install by package version:
library("remotes")
install_version("calibmsm", "1.1.3") Attach the package and use:
library("calibmsm")
Maintained by
Alexander Pate
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-11-30
Latest Update: 2025-06-13
Description:
Assess the calibration of an existing (i.e. previously developed) multistate
model through calibration plots.
Calibration is assessed using one of three methods. 1) Calibration methods for
binary logistic regression models applied at a fixed time point in conjunction
with inverse probability of censoring weights. 2) Calibration methods for
multinomial logistic regression models applied at a fixed time point in conjunction
with inverse probability of censoring weights. 3) Pseudo-values estimated using
the Aalen-Johansen estimator of observed risk. All methods are applied in conjunction
with landmarking when required. These calibration plots evaluate the calibration
(in a validation cohort of interest) of the transition probabilities estimated from an
existing multistate model. While package development has focused on multistate
models, calibration plots can be produced for any model which utilises information
post baseline to update predictions (e.g. dynamic models); competing risks models;
or standard single outcome survival models, where predictions can be made at
any landmark time. The underpinning methodology is currently undergoing peer review; see Pate et al. (2023)
and Pate et al. (2023) .
How to cite:
Alexander Pate (2023). calibmsm: Calibration Plots for the Transition Probabilities from Multistate Models. R package version 1.1.3, https://cran.r-project.org/web/packages/calibmsm. Accessed 05 Aug. 2026.
Previous versions and publish date:
Other packages that cited calibmsm R package
View calibmsm citation profile
Other R packages that calibmsm depends,
imports, suggests or enhances
Complete documentation for calibmsm
Functions, R codes and Examples using
the calibmsm R package
Some associated functions: calc_aj . calc_pv_aj . calc_weights . calib_blr . calib_mlr . calib_pv . calibmsm-package . ebmtcal . extract_ids_states . msebmtcal.cmprsk . msebmtcal . plot.calib_blr . plot.calib_mlr . plot.calib_pv . tp.cmprsk.j0 . tps0 . tps100 .
Some associated R codes: calib_blr.R . calib_mlr.R . calib_pv.R . calibmsm-misc.R . calibmsm-package.R . data.R . extract_ids_states.R . plot_calib.R . weights.R . Full calibmsm package functions and examples
Downloads during the last 30 days
Today's Hot Picks in Authors and Packages
dcov
A Fast Implementation of Distance Covariance
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Hang Weiqiang (view profile)
kernelPSI
Post-Selection Inference for Nonlinear Variable Selection
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Lotfi Slim (view profile)
quickcode
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
noisyr
Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput
sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Ilias Moutsopoulos (view profile)
dhReg
Dynamic Harmonic Regression
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Pranay Gaikwad (view profile)
28,083
R Packages
239,283
Dependencies
74,457
Author Associations
28,084
Publication Badges
