Time Dependent Shared Frailty Cox Model

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Documentation for package ‘TimeDepFrail’ version 0.0.1

• DESCRIPTION file.

Help Pages

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
coef.AdPaik	Extracts the optimal parameters of each cateogry for the 'Adapted Paik et al.' Model
coefse	Extracts the standard errors computed for each cateogry for the 'Adapted Paik et al.' Model
confint.AdPaik	Extracts the confidence intervals computed for each cateogry for the 'Adapted Paik et al.' Model
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
plot_survival	Plot of Conditional Survival Function
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	Summary of the Adapted Paik et al.'s Time-Dependent Shared Frailty Model
survival	Compute the Conditional Survival Function
time_int_eval	Resolution of integral with respect to time