summarise_analysis: Summarise analyses of simulations of time-to-event data using...

View source: R/simulation_functions.R

summarise_analysisR Documentation

Summarise analyses of simulations of time-to-event data using arbitrary event, censoring and recruitment distributions.

Description

Function for summarising the analyses of simulated time-to-event trial data produced by analyse_sim().
Automatically reads in format from analyse_sim(); no other input format is supported.
It automatically detects types of analysis performed and provides relevant summaries (log-rank, Cox, RMST, landmark).

Usage

summarise_analysis(analysed_results, alpha1 = 0.025)

Arguments

analysed_results

Output file from analyse_sim(). Only analyse_sim() output is supported.

alpha1

1-sided alpha to be used for analysis. Default=0.025.

Value

Returns a table with one row. Table contains the following columns:

  • "Simulations" Number of simulations conducted

  • "HR" Exponent of Mean Cox Log Hazard Ratio (LR/Cox analysis only)

  • "LogHR" Mean Cox Log Hazard Ratio (LR/Cox analysis only)

  • "LogHR_SE" Root mean square of the Cox Standard Errors for Log Hazard Ratio (LR/Cox analysis only)

  • "HR_Z" Mean Cox Z-Score (LR/Cox analysis only)

  • "HR_P" p-value of Mean Cox Z-Score (LR/Cox analysis only)

  • "HR_Power" Simulated power of Cox-regression (LR/Cox analysis only)

  • "HR_Failed" Proportion of simulations failing to calculate a Cox HR (LR/Cox analysis only)

  • "LR_Z" Mean Log-Rank Test Z-Score (LR/Cox analysis only)

  • "LR_P" p-value of Mean Log-Rank Test Z-Score (LR/Cox analysis only)

  • "LR_Power" Simulated power of the log-rank test (LR/Cox analysis only)

  • "LR_Failed" Proportion of simulations failing to calculate a log-rank test statistic (LR/Cox analysis only)

  • "Events_Active" Mean events in active arm (LR/Cox analysis only)

  • "Events_Control" Mean events in control arm (LR/Cox analysis only)

  • "Events_Total" Mean total events(LR/Cox analysis only)

  • "RMST_Time" Restriction time for RMST analysis (RMST analysis only)

  • "RMST_Control" Mean RMST for active arm (RMST analysis only)

  • "RMST_C_SE" Root mean square of RMST Standard Errors for active arm (RMST analysis only)

  • "RMST_Active" Mean RMST for control arm (RMST analysis only)

  • "RMST_A_SE" Root mean square of RMST Standard Errors for control arm (RMST analysis only)

  • "RMST_Delta" Mean RMST difference between arms active-control (RMST analysis only)

  • "RMST_D_SE" Root mean square of RMST difference Standard Errors (RMST analysis only)

  • "RMST_Power" Simulated power of RMST (RMST analysis only)

  • "RMST_Failed" Proportion of simulations failing to calculate the RMST (RMST analysis only)

  • "LM_Time" Landmark analysis time, i.e. assessment time of Survival function (Landmark analysis only)

  • "LM_Control" Mean survival function for active arm at landmark time (Landmark analysis only)

  • "LM_C_SE" Root mean square of Greenwood standard errors for active arm at landmark time (Landmark analysis only)

  • "LM_Active" Mean survival function for control arm at landmark time (Landmark analysis only)

  • "LM_A_SE" Root mean square of Greenwood standard errors for control arm at landmark time (Landmark analysis only)

  • "LM_Delta" Mean survival function difference active-control at landmark time (Landmark analysis only)

  • "LM_D_SE" Root mean square of Greenwood standard errors for survival differences at landmark time (Landmark analysis only)

  • "LM_Power" Power of landmark analysis (Landmark analysis only)

  • "LM_Failed" Proportion of simulations failing to calculate the survival difference at landmark time (Landmark analysis only)

Author(s)

James Bell

Examples

example_sim <- simulate_trials(active_ecurve=Weibull(250,0.8),control_ecurve=Weibull(100,1),
rcurve=LinearR(12,100,100), assess=40, iterations=5,seed=12345,detailed_output=TRUE)

example_analysis1 <- analyse_sim(example_sim)
example_analysis2 <- analyse_sim(data=example_sim,RMST=30,landmark=30)

example_summary1 <- summarise_analysis(example_analysis1)
example_summary2 <- summarise_analysis(example_analysis2)

gestate documentation built on April 26, 2023, 5:10 p.m.