compute_detection_probability_single

Compute Detection Probability for Single Theta (Internal)

internal

Implements statistical methods for exploratory subgroup identification
in clinical trials with survival endpoints. Provides tools for identifying
patient subgroups with differential treatment effects using machine learning
approaches including Generalized Random Forests (GRF), LASSO regularization,
and exhaustive combinatorial search algorithms. Features bootstrap bias
correction using infinitesimal jackknife methods to address selection bias
in post-hoc analyses. Designed for clinical researchers conducting exploratory
subgroup analyses in randomized controlled trials, particularly for
multi-regional clinical trials (MRCT) requiring regional consistency
evaluation. Supports both accelerated failure time (AFT) and Cox proportional
hazards models with comprehensive diagnostic and visualization tools.
Methods are described in León et al. (2024) <doi:10.1002/sim.10163>.

Larry Leon

forestsearch

Exploratory Subgroup Identification in Clinical Trials with
Survival Endpoints

compute_detection_probability_single function

<dl><dt>theta</dt>
<dd>Numeric. True hazard ratio in the subgroup. Can be a vector
for computing detection probability across multiple HR values.</dd>
<dt>n_sg</dt>
<dd>Integer. Subgroup sample size.</dd>
<dt>prop_cens</dt>
<dd>Numeric. Proportion censored (0-1). Default: 0.3</dd>
<dt>k_avg</dt>
<dd>Log of hr_threshold</dd>
<dt>k_ind</dt>
<dd>Log of hr_consistency</dd>
<dt>method</dt>
<dd>Character. Integration method: "cubature" (recommended for
accuracy) or "monte_carlo" (faster for exploration). Default: "cubature"</dd>
<dt>n_mc</dt>
<dd>Integer. Number of Monte Carlo samples if method = "monte_carlo".
Default: 100000</dd>
<dt>tol</dt>
<dd>Numeric. Relative tolerance for cubature integration.
Default: 1e-4</dd></dl>

Arguments

Compute Detection Probability for Single Theta (Internal) — compute_detection_probability_single

<dl>

<dt>theta</dt>
<dd>Numeric. True hazard ratio in the subgroup. Can be a vector
for computing detection probability across multiple HR values.</dd>


<dt>n_sg</dt>
<dd>Integer. Subgroup sample size.</dd>


<dt>prop_cens</dt>
<dd>Numeric. Proportion censored (0-1). Default: 0.3</dd>


<dt>k_avg</dt>
<dd>Log of hr_threshold</dd>


<dt>k_ind</dt>
<dd>Log of hr_consistency</dd>


<dt>method</dt>
<dd>Character. Integration method: "cubature" (recommended for
accuracy) or "monte_carlo" (faster for exploration). Default: "cubature"</dd>


<dt>n_mc</dt>
<dd>Integer. Number of Monte Carlo samples if method = "monte_carlo".
Default: 100000</dd>


<dt>tol</dt>
<dd>Numeric. Relative tolerance for cubature integration.
Default: 1e-4</dd>

</dl>

compute_detection_probability_single: Compute Detection Probability for Single Theta (Internal)

Description

Usage

Value

Arguments