Package: TimeDepFrail 0.0.1

TimeDepFrail: Time Dependent Shared Frailty Cox Model

Fits time-dependent shared frailty Cox model (specifically the adapted Paik et al.'s Model) based on the paper "Centre-Effect on Survival After Bone Marrow Transplantation: Application of Time-Dependent Frailty Models", by C.M. Wintrebert, H. Putter, A.H. Zwinderman and J.C. van Houwelingen (2004) <doi:10.1002/bimj.200310051>.

Authors:Alessandra Ragni [aut, cre], Giulia Romani [aut], Chiara Masci [aut]

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TimeDepFrail.pdf |TimeDepFrail.html✨
TimeDepFrail/json (API)

# Install 'TimeDepFrail' in R:
install.packages('TimeDepFrail', repos = c('https://alessandragni.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/alessandragni/timedepfrail/issues

Pkgdown site:https://alessandragni.github.io

On CRAN:

3.74 score 1 scripts 296 downloads 13 exports 0 dependencies

Last updated 1 months agofrom:4dd9efa348. Checks:8 OK. Indexed: yes.

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Doc / VignettesOKFeb 16 2025
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R-4.4-winOKFeb 16 2025
R-4.4-macOKFeb 16 2025
R-4.3-winOKFeb 16 2025
R-4.3-macOKFeb 16 2025

Exports:AdPaik_1DAdPaikModelcoefsefrailty_sdfrailty_sd.AdPaikplot_bas_hazardplot_frailty_sdplot_ll_1Dplot_ll_1D.AdPaikplot_post_frailty_estplot_survivalsummarysurvival

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
One-dimensional analysis of log-likelihood functionAdPaik_1D
Adapted Paik et al.'s Model: Time-Dependent Shared Frailty Cox ModelAdPaikModel
Baseline hazard step-functionbas_hazard
Check positiveness of the multiplicative constant Ccheck.C_mult
Check correctness of parameters categoriescheck.categories_params
Check correctness for the cluster variablecheck.centre
Check presence of null or nan element value in the datasetcheck.dataset
Check coherence between flag for optimal parameters and optimal parameterscheck.flag_optimal_params
Check correctness of formula termscheck.formula_terms
Check correctness of frailty standard deviationcheck.frailty_dispersion
Check existence of provided input indexcheck.index
Check correctness of plot variables pch and colorcheck.pchtype_colorbg
Check positiviness of the frailty standard deviationcheck.pos_frailty_sd
Check correctness of legend positioncheck.poslegend
Check numerosity of posterior frailty estimatescheck.post_frailty_centre
Check correctness of input parameterscheck.range_params
Check structure of the 'AdPaikModel' outputcheck.result.AdPaik
Check structure for the Parameters Confidence Intervalcheck.structure_paramsCI
Check structure of Posterior Frailty Confidence Intervalcheck.structure_post_frailty_CI
Check structure of Posterior Frailty Estimatescheck.structure_post_frailty_est
Check structure of Posterior Frailty Variancescheck.structure_post_frailty_var
Check correctness of time domain subdivisioncheck.time_axis
Check non-negativeness of the posterior frailty estimatescheck.value_post_frailty
Extracts the optimal parameters of each cateogry for the 'Adapted Paik et al.' Modelcoef.AdPaik
Extracts the standard errors computed for each cateogry for the 'Adapted Paik et al.' Modelcoefse
Extracts the confidence intervals computed for each cateogry for the 'Adapted Paik et al.' Modelconfint.AdPaik
Data Dropout Datasetdata_dropout
Transform categorical covariate into dummy variablesextract_dummy_variables
Extracting variables for Posterior Frailty Estimates computationextract_event_data
Frailty standard deviation and Variance for the 'Adapted Paik et al.'s Model'frailty_sd
Frailty standard deviation and Variance for the 'Adapted Paik et al.'s Model'frailty_sd.AdPaik
One-dimensional log-likelihood function to be optimized.ll_AdPaik_1D
One-dimensional group log-likelihood function.ll_AdPaik_centre_1D
Evaluation of model group log-likelihoodll_AdPaik_centre_eval
Evaluation of model log-likelihoodll_AdPaik_eval
Nodes and weights for the Gauss_hermite quadrature formula for the 'Centre-Specific Frailty Model with Power Parameter'. The nodes and weights have been extracted from the 'Handbook of Mathematical functions' pag 940.n_nodes
Nodes and weights for the Gauss-Hermite quadrature formula, for the 'Stochastic Time-Dependent Centre-Specific Frailty Model'. For the G function, the chosen nodes should not contain the zero (node) since it appears at the denominator of a fraction. Also in this case, the nodes and weights have been extracted from the 'Handbook of Mathematical functions', pag 940.n_nodesG
Confidence interval for the optimal estimated parametersparams_CI
Standard error of the parametersparams_se.AdPaik
Plot the Baseline Hazard Step-Functionplot_bas_hazard
Plot for the Frailty Standard Deviation or Varianceplot_frailty_sd
Plot the One-Dimensional Log-Likelihood Functionplot_ll_1D
Plot the One-Dimensional Log-Likelihood Functionplot_ll_1D.AdPaik
Plot the Posterior Frailty Estimatesplot_post_frailty_est
Plot of Conditional Survival Functionplot_survival
Confidence interval for posterior frailty estimatespost_frailty_CI.AdPaik
Posterior frailty estimates and variances for the 'Adapted Paik et al.'s Model'post_frailty.AdPaik
Summary for Time-Dependent Frailty Modelssummary
Summary of the Adapted Paik et al.'s Time-Dependent Shared Frailty Modelsummary.AdPaik
Compute the Conditional Survival Functionsurvival
Resolution of integral with respect to timetime_int_eval