Package: mets
Type: Package
Title: Analysis of Multivariate Event Times
Version: 1.1.1
Date: 2015-05-27
Author: Klaus K. Holst and Thomas Scheike
Maintainer: Klaus K. Holst <klaus@holst.it>
Description: Implementation of various statistical models for multivariate
event history data. Including multivariate cumulative incidence models, and
bivariate random effects probit models (Liability models). Also contains
two-stage binomial modelling that can do pairwise odds-ratio dependence
modelling based marginal logistic regression models. This is an alternative
to the alternating logistic regression approach (ALR).
License: GPL (>= 2)
LazyLoad: yes
URL: http://lava.r-forge.r-project.org/
Depends: R (>= 2.15), timereg (>= 1.8.9), lava (>= 1.4)
Imports: numDeriv, compiler, Rcpp, splines, survival
Suggests: lava.tobit (>= 0.4-7), prodlim, testthat, ucminf
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2015-05-28 17:17:19 UTC; klaus
Repository: CRAN
Date/Publication: 2015-05-29 07:36:10
Package: ROCt
Type: Package
Title: Time-Dependent ROC Curve Estimators and Expected Utility
Functions
Version: 0.9.4
Date: 2016-03-09
Author: Y. Foucher, E. Dantan, P. Tessier, F. Le Borgne, and M. Lorent
Maintainer: Y. Foucher <Yohann.Foucher@univ-nantes.fr>
Description: Contains functions in order to estimate diagnostic and prognostic capacities of continuous markers. More precisely, one function concerns the estimation of time-dependent ROC (ROCt) curve, as proposed by Heagerty et al. (2000) <DOI: 10.1111/j.0006-341X.2000.00337.x>. One function concerns the adaptation of the ROCt theory for studying the capacity of a marker to predict the excess of mortality of a specific population compared to the general population. This last part is based on additive relative survival models and the work of Pohar-Perme et al. (2012) <DOI: 10.1111/j.1541-0420.2011.01640.x>. We also propose two functions for cut-off estimation in medical decision making by maximizing time-dependent expected utility function. Finally, we propose confounder-adjusted estimators of ROC and ROCt curves by using the Inverse Probability Weighting (IPW) approach. For the confounder-adjusted ROC curve (without censoring), we also proposed the implementation of the estimator based on placement values proposed by Pepe and Cai (2004) <DOI: 10.1111/j.0006-341X.2004.00200.x>.
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 2.10), splines, date, survival, relsurv, timereg
URL: www.r-project.org, www.divat.fr
Packaged: 2016-03-09 14:22:03 UTC; Yohann
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2016-03-09 23:12:21
providing 
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