R version 4.6.0 RC (2026-04-17 r89914 ucrt) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(RMSTpowerBoost)
> 
> test_check("RMSTpowerBoost")
--- Calculating Power (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ arm
Simulating for n = 100 /arm ...
Total simulation time: 6.4 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |      Value|
|:--------------------|----------:|
|Mean RMST Difference |  0.1606860|
|Mean Standard Error  |  0.6608699|
|95% CI Lower         | -1.4340329|
|95% CI Upper         |  1.7554049|
--- Calculating Power (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ region + arm:region
Simulating for n = 50 /stratum ...
Total simulation time: 4.52 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Searching for Sample Size (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ arm
  N = 50/arm, Calculating Power... Power = 0
  N = 100/arm, Calculating Power... Power = 0
  N = 150/arm, Calculating Power... Power = 0.1
Success: Target power reached at N = 150/arm.
Total simulation time: 19.73 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |      Value|
|:--------------------|----------:|
|Mean RMST Difference |  0.3426445|
|Mean Standard Error  |  0.5508833|
|95% CI Lower         | -0.5573381|
|95% CI Upper         |  1.2426271|
--- Estimating parameters from pilot data... ---
--- Estimating additive effect via stratum-centering... ---
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data for analytic search... ---
--- Searching for Sample Size (Method: Additive Analytic) ---
  N = 50/stratum, Calculated Power = 1

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Stratum|
|------------:|----------------------:|
|          0.8|                     50|
--- Estimating parameters from pilot data for analytic calculation... ---
Model: Y_rmst ~ factor(arm) + age
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data for analytic search... ---
Model: Y_rmst ~ factor(arm) + age
--- Searching for Sample Size (Method: Analytic) ---
  N = 10/arm, Calculated Power = 0.056

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|            0|                 10|

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|            0|                 10|
--- Estimating parameters from pilot data... ---
--- Estimating additive effect via stratum-centering... ---
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data for analytic search... ---
--- Searching for Sample Size (Method: Additive Analytic) ---
  N = 10/stratum, Calculated Power = 0.062

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Stratum|
|------------:|----------------------:|
|            0|                     10|
--- Estimating parameters from pilot data (log-linear approximation)... ---
Approximation Model: log(Y_rmst) ~ arm + age + region
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data (log-linear approximation)... ---
--- Searching for Sample Size (Method: Analytic/Approximation) ---
  N = 10/stratum, Calculated Power = 0.033

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Stratum|
|------------:|----------------------:|
|            0|                     10|
--- Calculating Power (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ region + arm:region + age
Simulating for n = 8 /stratum ...
Total simulation time: 0.42 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Searching for Sample Size (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ region + arm:region + age
  N = 8/stratum, Calculating Power... Power = 0
Success: Target power reached at N = 8/stratum.
Total simulation time: 0.54 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Calculating Power (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm + age
Simulating for n = 8 per arm...
Total simulation time: 0.08 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |      Value|
|:--------------------|----------:|
|Mean RMST Difference |  0.0615712|
|Mean Standard Error  |  1.0135833|
|95% CI Lower         | -0.5825562|
|95% CI Upper         |  0.7056986|
--- Searching for Sample Size (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm + age

--- Searching for N for 0% Power ---
  N = 8/arm, Calculated Power = 0.5
Success: Target power reached at N = 8/arm.
Total simulation time: 0.07 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |     Value|
|:--------------------|---------:|
|Mean RMST Difference |  2.309706|
|Mean Standard Error  |  1.394894|
|95% CI Lower         | -2.571851|
|95% CI Upper         |  7.191264|
Model: log(pseudo_obs) ~ region + region:arm + age
--- Calculating Power (Method: Multiplicative Stratified RMST Model) ---
Simulating for n = 8/stratum...
Total simulation time: 0.12 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Ratio)

|      |Statistic       |     Value|
|:-----|:---------------|---------:|
|      |Mean RMST Ratio | 0.8356950|
|2.5%  |95% CI Lower    | 0.6233788|
|97.5% |95% CI Upper    | 1.0480112|
Model: log(pseudo_obs) ~ region + region:arm + age
--- Searching for Sample Size (Method: Multiplicative Stratified RMST Model) ---
  N = 8/stratum, Calculating Power... Power = 0
Success: Target power reached at N = 8/stratum.
Total simulation time: 0.12 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Ratio)

|      |Statistic       |     Value|
|:-----|:---------------|---------:|
|      |Mean RMST Ratio | 0.7489890|
|2.5%  |95% CI Lower    | 0.6895765|
|97.5% |95% CI Upper    | 0.8084014|
--- Calculating Power (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ region + arm:region + s(age)
Simulating for n = 5 /stratum ...
Total simulation time: 0.41 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Calculating Power (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm + age
Simulating for n = 5 per arm...
Total simulation time: 0.1 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |     Value|
|:--------------------|---------:|
|Mean RMST Difference | 0.4171680|
|Mean Standard Error  | 0.6495934|
|95% CI Lower         | 0.1721532|
|95% CI Upper         | 0.6621828|
--- Calculating Power (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm
Simulating for n = 6 per arm...
Total simulation time: 0.05 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Searching for Sample Size (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm

--- Searching for N for 95% Power ---
  N = 4/arm, Calculated Power = 0
  N = 6/arm, Calculated Power = 0
Total simulation time: 0.07 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Estimating parameters from pilot data (log-linear approximation)... ---
--- Searching for Sample Size (Method: Analytic/Approximation) ---
  N = 4/stratum, Calculated Power = 0.075
  N = 6/stratum, Calculated Power = 0.093

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Stratum|
|------------:|----------------------:|
|        0.999|                      6|
--- Estimating parameters from pilot data (log-linear approximation)... ---
Approximation Model: log(Y_rmst) ~ arm + region
Model: log(pseudo_obs) ~ region + region:arm
--- Searching for Sample Size (Method: Multiplicative Stratified RMST Model) ---
  N = 4/stratum, Calculating Power... Power = 0
  N = 6/stratum, Calculating Power... Power = 0.5
Total simulation time: 0.16 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Ratio)

|      |Statistic       |     Value|
|:-----|:---------------|---------:|
|      |Mean RMST Ratio | 0.8351507|
|2.5%  |95% CI Lower    | 0.5898167|
|97.5% |95% CI Upper    | 1.0804848|
--- Calculating Power (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ region + arm:region + x1
Simulating for n = 4 /stratum ...
Total simulation time: 0.37 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Searching for Sample Size (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ region + arm:region + x1
  N = 4/stratum, Calculating Power... Power = 0
  N = 5/stratum, Calculating Power... Power = 0
Total simulation time: 1.07 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Searching for Sample Size (Method: Additive GAM for RMST) ---
Model: pseudo_obs ~ region + arm:region + x1
  N = 4/stratum, Calculating Power... Power = 0
  N = 5/stratum, Calculating Power... Power = 0
Total simulation time: 1.02 seconds

--- Simulation Summary ---
No valid estimates were generated to create a summary.
--- Calculating Power (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm + age
Simulating for n = 100 per arm...
Simulating for n = 150 per arm...
Total simulation time: 0.17 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |      Value|
|:--------------------|----------:|
|Mean RMST Difference | -0.9337539|
|Mean Standard Error  |  0.8597627|
|95% CI Lower         | -2.1021349|
|95% CI Upper         |  0.2346271|
--- Searching for Sample Size (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm

--- Searching for N for 60% Power ---
  N = 100/arm, Calculated Power = 1
Success: Target power reached at N = 100/arm.
Total simulation time: 0.11 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |    Value|
|:--------------------|--------:|
|Mean RMST Difference | 4.953698|
|Mean Standard Error  | 1.009197|
|95% CI Lower         | 2.577716|
|95% CI Upper         | 7.329681|
--- Estimating parameters from pilot data for analytic calculation... ---
Model: Y_rmst ~ factor(arm) + age
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data for analytic search... ---
Model: Y_rmst ~ factor(arm)
--- Searching for Sample Size (Method: Analytic) ---
  N = 50/arm, Calculated Power = 0.916

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|          0.8|                 50|
--- Estimating parameters from pilot data for analytic search... ---
Model: Y_rmst ~ factor(arm)
--- Searching for Sample Size (Method: Analytic) ---
  N = 50/arm, Calculated Power = 0.916

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|          0.7|                 50|
--- Calculating Power (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm
Simulating for n = 50 per arm...
Total simulation time: 0.52 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |    Value|
|:--------------------|--------:|
|Mean RMST Difference | 4.903786|
|Mean Standard Error  | 1.417759|
|95% CI Lower         | 1.705048|
|95% CI Upper         | 8.102524|
--- Estimating parameters from pilot data for analytic calculation... ---
Model: Y_rmst ~ factor(arm) + age
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Calculating Power (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm + age
Simulating for n = 20 per arm...
Total simulation time: 0.06 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |      Value|
|:--------------------|----------:|
|Mean RMST Difference |  0.5427850|
|Mean Standard Error  |  0.5262415|
|95% CI Lower         | -0.1030334|
|95% CI Upper         |  1.1886034|
--- Estimating parameters from pilot data (log-linear approximation)... ---
Approximation Model: log(Y_rmst) ~ arm + age + region
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data (log-linear approximation)... ---
Approximation Model: log(Y_rmst) ~ arm + age + region
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data (log-linear approximation)... ---
Approximation Model: log(Y_rmst) ~ arm + age + region
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data for analytic search... ---
Model: Y_rmst ~ factor(arm) + age
--- Searching for Sample Size (Method: Analytic) ---
  N = 20/arm, Calculated Power = 0.028

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|         0.02|                 20|

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|          0.5|                250|
--- Estimating parameters from pilot data for analytic calculation... ---
Model: Y_rmst ~ factor(arm) + age
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data (log-linear approximation)... ---
Approximation Model: log(Y_rmst) ~ arm + age + region
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data for analytic search... ---
Model: Y_rmst ~ factor(arm) + age
--- Searching for Sample Size (Method: Analytic) ---
  N = 20/arm, Calculated Power = 0.028

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|         0.02|                 20|

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|          0.5|                250|
--- Estimating parameters from pilot data for analytic calculation... ---
Model: Y_rmst ~ factor(arm) + age
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data (log-linear approximation)... ---
Approximation Model: log(Y_rmst) ~ arm + age + region
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data for analytic search... ---
Model: Y_rmst ~ factor(arm) + age
--- Searching for Sample Size (Method: Analytic) ---
  N = 20/arm, Calculated Power = 0.028

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|         0.02|                 20|
--- Estimating parameters from pilot data for analytic calculation... ---
Model: Y_rmst ~ factor(arm) + age
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Calculating Power (Method: Linear RMST with IPCW) ---
Model: Y_rmst ~ arm + age
Simulating for n = 20 per arm...
Total simulation time: 0.08 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Difference)

|Statistic            |      Value|
|:--------------------|----------:|
|Mean RMST Difference |  0.0559245|
|Mean Standard Error  |  0.5686558|
|95% CI Lower         | -0.5592273|
|95% CI Upper         |  0.6710763|
--- Estimating parameters from pilot data for analytic search... ---
Model: Y_rmst ~ factor(arm) + age
--- Searching for Sample Size (Method: Analytic) ---
  N = 20/arm, Calculated Power = 0.028

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|         0.02|                 20|
--- Estimating parameters from pilot data for analytic calculation... ---
Model: Y_rmst ~ factor(arm) + age
--- Calculating asymptotic variance... ---
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data for analytic search... ---
Model: Y_rmst ~ factor(arm) + age
--- Searching for Sample Size (Method: Analytic) ---
  N = 20/arm, Calculated Power = 0.028

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|         0.02|                 20|
`geom_line()`: Each group consists of only one observation.
i Do you need to adjust the group aesthetic?

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|          0.5|                 75|

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|          0.7|                 50|

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|          0.7|                150|

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Arm|
|------------:|------------------:|
|          0.8|                300|
Model: log(pseudo_obs) ~ region + region:arm
--- Calculating Power (Method: Multiplicative Stratified RMST Model) ---
Simulating for n = 60/stratum...
Total simulation time: 5.34 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Ratio)

|      |Statistic       |     Value|
|:-----|:---------------|---------:|
|      |Mean RMST Ratio | 1.2609646|
|2.5%  |95% CI Lower    | 0.9479785|
|97.5% |95% CI Upper    | 1.6108678|
Model: log(pseudo_obs) ~ region + region:arm
--- Searching for Sample Size (Method: Multiplicative Stratified RMST Model) ---
  N = 50/stratum, Calculating Power... Power = 0.2
  N = 100/stratum, Calculating Power... Power = 0.6
  N = 150/stratum, Calculating Power... Power = 0.7
Success: Target power reached at N = 150/stratum.
Total simulation time: 33.46 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Ratio)

|      |Statistic       |    Value|
|:-----|:---------------|--------:|
|      |Mean RMST Ratio | 1.284136|
|2.5%  |95% CI Lower    | 1.205268|
|97.5% |95% CI Upper    | 1.417947|
--- Estimating parameters from pilot data (log-linear approximation)... ---
Approximation Model: log(Y_rmst) ~ arm + region
--- Calculating power for specified sample sizes... ---
--- Estimating parameters from pilot data (log-linear approximation)... ---
--- Searching for Sample Size (Method: Analytic/Approximation) ---
  N = 50/stratum, Calculated Power = 0.385
  N = 75/stratum, Calculated Power = 0.533
  N = 100/stratum, Calculated Power = 0.655
  N = 125/stratum, Calculated Power = 0.751
  N = 150/stratum, Calculated Power = 0.824

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Stratum|
|------------:|----------------------:|
|          0.8|                    150|
--- Estimating parameters from pilot data (log-linear approximation)... ---
--- Searching for Sample Size (Method: Analytic/Approximation) ---
  N = 50/stratum, Calculated Power = 0.385
  N = 75/stratum, Calculated Power = 0.533
  N = 100/stratum, Calculated Power = 0.655
  N = 125/stratum, Calculated Power = 0.751

--- Calculation Summary ---


Table: Required Sample Size

| Target_Power| Required_N_per_Stratum|
|------------:|----------------------:|
|          0.7|                    125|
Model: log(pseudo_obs) ~ region + region:arm
--- Calculating Power (Method: Multiplicative Stratified RMST Model) ---
Simulating for n = 125/stratum...
Total simulation time: 13.55 seconds

--- Simulation Summary ---


Table: Estimated Treatment Effect (RMST Ratio)

|      |Statistic       |    Value|
|:-----|:---------------|--------:|
|      |Mean RMST Ratio | 1.229257|
|2.5%  |95% CI Lower    | 1.164066|
|97.5% |95% CI Upper    | 1.348020|
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 485 ]
> 
> proc.time()
   user  system elapsed 
  97.59    2.31   99.90