- Referenced in 81 articles
- package timereg: Flexible regression models for survival data. Programs for Martinussen and Scheike (2006), ‘Dynamic ... Regression Models for Survival Data’, Springer ... Verlag. Plus more recent developments. Additive survival model, semiparametric proportional odds model, fast cumulative residuals...
- Referenced in 309 articles
- analysis of longitudinal and survival data, spatio-temporal models, graphical models, and semi-parametric statistics...
- Referenced in 85 articles
- models, elastic net, binomial and Cox survival model...
- Referenced in 128 articles
- drift) inverse Gaussian distribution to survival data. The model is described in Aalen OO, Borgan ... Gjessing HK. Survival and Event History Analysis. A Process Point of View. Springer ... been randomized with a Gaussian distribution. The model allows covariates to influence starting values...
- Referenced in 436 articles
- survival analysis, psychometric analysis, cluster analysis, and nonparametric analysis. A few examples include mixed models...
- Referenced in 197 articles
- penalised likelihood , survival analysis: descriptive statistics, two-sample tests, parametric accelerated failure models, Cox model...
- Referenced in 31 articles
- generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented...
- Referenced in 77 articles
- dependent variable models, including models for binary, censored, truncated, survival, count, discrete and continuous variables...
- Referenced in 160 articles
- models for conditional quantiles of a univariate response and several methods for handling censored survival...
- Referenced in 22 articles
- regression parameters from linear and survival models as well as those based on correlation parameters...
- Referenced in 28 articles
- proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation...
- Referenced in 43 articles
- model and Cox proportional hazard model. Clustered and recurrent survival times can be studied ... approximated cross-validation procedure. 2) Additive frailty models for proportional hazard models with two correlated...
- Referenced in 12 articles
- linear models, generalizable linear models and survival models (cox regression...
- Referenced in 27 articles
- parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split ... Extensible functionality for visualizing tree-structured regression models is available...
- Referenced in 8 articles
- shared parameter joint models of longitudinal and survival data. stjm fits shared parameter joint models ... single survival outcome are allowed. A linear mixed effects model is used for the longitudinal ... hazards models. Furthermore, the flexible parametric survival model (see stpm2), modelled on the log cumulative ... joint likelihood. Under all survival submodels except the flexible parametric model, Gauss-Kronrod quadrature...
- Referenced in 9 articles
- parametric and semiparametric mixture cure models. Cure models have been developed to analyze failure time ... cured fraction. For such data, standard survival models are usually not appropriate because they ... semiparametric models can be used to model the survival of uncured individuals. The maximization ... performed using SAS PROC NLMIXED for parametric models and through an EM algorithm...
- Referenced in 9 articles
- package spBayesSurv. Provides several Bayesian survival models for spatial/non-spatial survival data: marginal Bayesian Nonparametric models...
- Referenced in 5 articles
- package rstpm2. Generalized Survival Models. R implementation of generalized survival models, where ... link function g, survival S at time t with covariates x and a linear predictor ... effect(s) are smooth. For fully parametric models, this re-implements Stata ... stpm2’ function, which are flexible parametric survival models developed by Royston and colleagues. We have...
- Referenced in 20 articles
- package flexsurv: Flexible Parametric Survival and Multi-State Models. Flexible parametric models for time...