Other packages > Find by keyword >

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", "1.1.1")



Attach the package and use:
library("calibmsm")
Maintained by
Alexander Pate
[Scholar Profile | Author Map]
First Published: 2023-11-30
Latest Update: 2023-11-30
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 1.1.1, https://cran.r-project.org/web/packages/calibmsm. Accessed 09 Apr. 2025.
Previous versions and publish date:
1.0.0 (2023-11-30 20:50), 1.1.0 (2024-05-13 13:33)
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
Downloads during the last 30 days
03/1003/1103/1203/1303/1403/1503/1603/1703/1803/1903/2003/2103/2203/2303/2403/2503/2603/2703/2803/2903/3003/3104/0104/0204/0304/0404/0504/0604/0704/08Downloads for calibmsm024681012141618TrendBars

Today's Hot Picks in Authors and Packages

MultSurvTests  
Permutation Tests for Multivariate Survival Analysis
Multivariate version of the two-sample Gehan and logrank tests, as described in L.J Wei & J.M Lachin ...
Download / Learn more Package Citations See dependency  
prettyglm  
Pretty Summaries of Generalized Linear Model Coefficients
One of the main advantages of using Generalised Linear Models is their interpretability. The goal ...
Download / Learn more Package Citations See dependency  
multitaper  
Spectral Analysis Tools using the Multitaper Method
Implements multitaper spectral analysis using discrete prolate spheroidal sequences (Slepians) and s ...
Download / Learn more Package Citations See dependency  
fisheye  
Transform Base Maps Using Log-Azimuthal Projection
Base maps are transformed to focus on a specific location using an azimuthal logarithmic distance t ...
Download / Learn more Package Citations See dependency  
cvmdisc  
Cramer von Mises Tests for Discrete or Grouped Distributions
Implements Cramer-von Mises Statistics for testing fit to (1) fully specified discrete distributions ...
Download / Learn more Package Citations See dependency  
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  

24,012

R Packages

207,311

Dependencies

64,867

Author Associations

24,013

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA