Time Dependent Shared Frailty Cox Model

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Documentation for package ‘TimeDepFrail’ version 0.0.0.9

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AdPaikModel Adapted Paik et al.'s Model: Time-Dependent Shared Frailty Cox Model
AdPaik_1D One-dimensional analysis of log-likelihood function
bas_hazard Baseline hazard step-function
check.categories_params Check correctness of parameters categories
check.centre Check correctness for the cluster variable
check.C_mult Check positiveness of the multiplicative constant C
check.dataset Check presence of null or nan element value in the dataset
check.flag_optimal_params Check coherence between flag for optimal parameters and optimal parameters
check.formula_terms Check correctness of formula terms
check.frailty_dispersion Check correctness of frailty standard deviation
check.index Check existence of provided input index
check.pchtype_colorbg Check correctness of plot variables pch and color
check.poslegend Check correctness of legend position
check.post_frailty_centre Check numerosity of posterior frailty estimates
check.pos_frailty_sd Check positiviness of the frailty standard deviation
check.range_params Check correctness of input parameters
check.result.AdPaik Check structure of the 'AdPaikModel' output
check.structure_paramsCI Check structure for the Parameters Confidence Interval
check.structure_post_frailty_CI Check structure of Posterior Frailty Confidence Interval
check.structure_post_frailty_est Check structure of Posterior Frailty Estimates
check.structure_post_frailty_var Check structure of Posterior Frailty Variances
check.time_axis Check correctness of time domain subdivision
check.value_post_frailty Check non-negativeness of the posterior frailty estimates
data_dropout Data Dropout Dataset
extract_dummy_variables Transform categorical covariate into dummy variables
extract_event_data Extracting variables for Posterior Frailty Estimates computation
frailty_sd Frailty standard deviation and Variance for the 'Adapted Paik et al.'s Model'
frailty_sd.AdPaik Frailty standard deviation and Variance for the 'Adapted Paik et al.'s Model'
ll_AdPaik_1D One-dimensional log-likelihood function to be optimized.
ll_AdPaik_centre_1D One-dimensional group log-likelihood function.
ll_AdPaik_centre_eval Evaluation of model group log-likelihood
ll_AdPaik_eval Evaluation of model log-likelihood
n_nodes 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_nodesG 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.
params_CI Confidence interval for the optimal estimated parameters
params_se.AdPaik Standard error of the parameters
plot_bas_hazard Plot the Baseline Hazard Step-Function
plot_frailty_sd Plot for the Frailty Standard Deviation or Variance
plot_ll_1D Plot the One-Dimensional Log-Likelihood Function
plot_ll_1D.AdPaik Plot the One-Dimensional Log-Likelihood Function
plot_post_frailty_est Plot the Posterior Frailty Estimates
post_frailty.AdPaik Posterior frailty estimates and variances for the 'Adapted Paik et al.'s Model'
post_frailty_CI.AdPaik Confidence interval for posterior frailty estimates
summary Summary for Time-Dependent Frailty Models
summary.AdPaik SSummary of the Adapted Paik et al.'s Time-Dependent Shared Frailty Model
time_int_eval Resolution of integral with respect to time