Simulate Non-Proportional Hazards

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Documentation for package ‘SimNPH’ version 0.5.6

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admin_censoring_events Add recruitment time to Dataset
admin_censoring_time Add recruitment time to Dataset
analyse_aft Analyse Dataset with accelarated failure time models
analyse_ahr Analyse the dataset using extimators for the the average hazard ratio
analyse_coxph Analyse Dataset with the Cox Protportional Hazards Model
analyse_describe Create a Function for Descriptive Statistics of a Dataset
analyse_diff_median_survival Analyse the dataset using differnce in median survival
analyse_gehan_wilcoxon Create Analyse function for Gehan Wilcoxon test
analyse_group_sequential Create Analyse Functions for Group Sequential Design
analyse_logrank Analyse Dataset with the Logrank Test
analyse_logrank_fh_weights Analyse Dataset with the Fleming Harrington weighted Logrank Test
analyse_maxcombo Analyse Dataset with the Maxcombo Test
analyse_milestone_survival Analyse the Dataset using difference or quotient of milestone survival
analyse_modelstly_weighted Create Analyse function for the modestly weighted logrank test
analyse_piecewise_exponential Create Analyse function for piecewise exponential model
analyse_rmst_diff Analyse the Dataset using the difference in RMST
analyse_weibull Analyse Dataset with Weibull Regression
assumptions_crossing_hazards Generate Dataset with crossing hazards
assumptions_delayed_effect Generate Dataset with delayed effect
assumptions_progression Create an empty assumtions data.frame for generate_progression
assumptions_subgroup Generate Dataset with different treatment effect in subgroup
cen_rate_from_cen_prop_crossing_hazards Generate Dataset with crossing hazards
cen_rate_from_cen_prop_delayed_effect Generate Dataset with delayed effect
cen_rate_from_cen_prop_progression Create an empty assumtions data.frame for generate_progression
cen_rate_from_cen_prop_subgroup Generate Dataset with different treatment effect in subgroup
combination_tests_delayed Results of an example simulation
combined_plot Functions for Plotting and Reporting Results
create_summarise_function Create a summarise function from a named list of functions
d2m Functions to Convert Between Days and Months and Medians and Rates
design_fixed_followup Create a data.frame with an example fixed design
design_group_sequential Create a data.frame with an example group sequential design
generate_crossing_hazards Generate Dataset with crossing hazards
generate_delayed_effect Generate Dataset with delayed effect
generate_progression Create an empty assumtions data.frame for generate_progression
generate_subgroup Generate Dataset with different treatment effect in subgroup
hazard_before_progression_from_PH_effect_size Create an empty assumtions data.frame for generate_progression
hazard_subgroup_from_PH_effect_size Generate Dataset with different treatment effect in subgroup
hr_after_crossing_from_PH_effect_size Generate Dataset with crossing hazards
hr_after_onset_from_PH_effect_size Generate Dataset with delayed effect
labs_from_labels Add ggplot axis labels from labels attribute
m2d Functions to Convert Between Days and Months and Medians and Rates
m2r Functions to Convert Between Days and Months and Medians and Rates
merge_additional_results Merge results from additional or updated simulations
mixture_cdf_fun Fast implementation of hazard, cumulative hazard, ... for mixtures of subpopulations
mixture_cumhaz_fun Fast implementation of hazard, cumulative hazard, ... for mixtures of subpopulations
mixture_haz_fun Fast implementation of hazard, cumulative hazard, ... for mixtures of subpopulations
mixture_pdf_fun Fast implementation of hazard, cumulative hazard, ... for mixtures of subpopulations
mixture_quant_fun Fast implementation of hazard, cumulative hazard, ... for mixtures of subpopulations
mixture_rng_fun Fast implementation of hazard, cumulative hazard, ... for mixtures of subpopulations
mixture_surv_fun Fast implementation of hazard, cumulative hazard, ... for mixtures of subpopulations
progression_cdf_fun Fast implementation of cumulative density function, survival function, ... for scenarios with progression
progression_haz_fun Fast implementation of cumulative density function, survival function, ... for scenarios with progression
progression_pdf_fun Fast implementation of cumulative density function, survival function, ... for scenarios with progression
progression_quant_fun Fast implementation of cumulative density function, survival function, ... for scenarios with progression
progression_rate_from_progression_prop Create an empty assumtions data.frame for generate_progression
progression_surv_fun Fast implementation of cumulative density function, survival function, ... for scenarios with progression
r2m Functions to Convert Between Days and Months and Medians and Rates
random_censoring_exp Apply Random Exponentially Distributed Censoring
recruitment_uniform Add recruitment time to Dataset
rename_results_column Rename Columns in Simulation Results and Update Attributes
rename_results_column_pattern Rename Columns in Simulation Results and Update Attributes
results_pivot_longer Functions for Plotting and Reporting Results
shhr_gg Plot of survival, hazard and hazard ratio of two groups as a function of time using ggplot and patchwork
summarise_describe Create a Function for Descriptive Statistics of a Dataset
summarise_estimator Generic Summarise function for esitmators
summarise_group_sequential Create Analyse Functions for Group Sequential Design
summarise_test Generic summarise function for tests
true_summary_statistics_crossing_hazards Generate Dataset with crossing hazards
true_summary_statistics_delayed_effect Generate Dataset with delayed effect
true_summary_statistics_progression Create an empty assumtions data.frame for generate_progression
true_summary_statistics_subgroup Generate Dataset with different treatment effect in subgroup
upsert_merge Merge results from additional or updated simulations
wrap_all_in_preserve_seed Wrappers around Analyse Functions
wrap_all_in_trycatch Wrappers around Analyse Functions