Package: TimeDepFrail 0.0.0.9

Alessandra Ragni

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 [ctb]

TimeDepFrail_0.0.0.9.tar.gz
TimeDepFrail_0.0.0.9.tar.gz(r-4.5-noble)TimeDepFrail_0.0.0.9.tar.gz(r-4.4-noble)
TimeDepFrail_0.0.0.9.tgz(r-4.4-emscripten)TimeDepFrail_0.0.0.9.tgz(r-4.3-emscripten)
TimeDepFrail.pdf |TimeDepFrail.html✨
TimeDepFrail/json (API)

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

Peer review:

Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 3 scripts 10 exports 0 dependencies

Last updated 12 hours agofrom:c3a2655336. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-linuxOKNov 22 2024

Exports:AdPaik_1DAdPaikModelfrailty_sdfrailty_sd.AdPaikplot_bas_hazardplot_frailty_sdplot_ll_1Dplot_ll_1D.AdPaikplot_post_frailty_estsummary

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
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
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
SSummary of the Adapted Paik et al.'s Time-Dependent Shared Frailty Modelsummary.AdPaik
Resolution of integral with respect to timetime_int_eval