obs_exampledata_train

Example training data for observational setting

Provides functions to assess complex heterogeneity in the strength of a surrogate marker with respect to multiple baseline covariates, in either a randomized treatment setting or observational setting. For a randomized treatment setting, the functions assess and test for heterogeneity using both a parametric model and a semiparametric two-step model. More details for the randomized setting are available in: Knowlton, R., Tian, L., & Parast, L. (2025). "A General Framework to Assess Complex Heterogeneity in the Strength of a Surrogate Marker," Statistics in Medicine, 44(5), e70001 <doi:10.1002/sim.70001>. For an observational setting, functions in this package assess complex heterogeneity in the strength of a surrogate marker using meta-learners, with options for different base learners. More details for the observational setting will be available in the future in: Knowlton, R., Parast, L. (2025) "Assessing Surrogate Heterogeneity in Real World Data Using Meta-Learners." A tutorial for this package can be found at <https://www.laylaparast.com/cohetsurr>.

Layla Parast

cohetsurr

Assessing Complex Heterogeneity in Surrogacy

Rebecca Knowlton

obs_exampledata_train function

A data frame with 1800 observations on the following 9 variables.<dl>
 <dt><code>X1</code></dt>
<dd>a numeric baseline covariate of interest</dd> <dt><code>X2</code></dt>
<dd>a numeric baseline covariate of interest</dd> <dt><code>X3</code></dt>
<dd>a numeric baseline covariate of interest</dd> <dt><code>X4</code></dt>
<dd>a numeric baseline covariate of interest</dd> <dt><code>X5</code></dt>
<dd>a numeric baseline covariate of interest</dd> <dt><code>X6</code></dt>
<dd>a numeric baseline covariate of interest</dd> <dt><code>G</code></dt>
<dd>the non-randomized treatment assignment, where 1 indicates treated and 0 indicates control</dd> <dt><code>S</code></dt>
<dd>the surrogate marker</dd> <dt><code>Y</code></dt>
<dd>the primary outcome</dd> 
</dl>

Format

Example training data for observational setting — obs_exampledata_train

A data frame with 1800 observations on the following 9 variables.<dl>
 <dt><code>X1</code></dt>
<dd>a numeric baseline covariate of interest</dd>

 <dt><code>X2</code></dt>
<dd>a numeric baseline covariate of interest</dd>

 <dt><code>X3</code></dt>
<dd>a numeric baseline covariate of interest</dd>

 <dt><code>X4</code></dt>
<dd>a numeric baseline covariate of interest</dd>

 <dt><code>X5</code></dt>
<dd>a numeric baseline covariate of interest</dd>

 <dt><code>X6</code></dt>
<dd>a numeric baseline covariate of interest</dd>

 <dt><code>G</code></dt>
<dd>the non-randomized treatment assignment, where 1 indicates treated and 0 indicates control</dd>

 <dt><code>S</code></dt>
<dd>the surrogate marker</dd>

 <dt><code>Y</code></dt>
<dd>the primary outcome</dd>

 
</dl>

obs_exampledata_train: Example training data for observational setting

Description

Usage

Arguments

Format

Examples