smoother_fitter

internal

Provides functions to nonparametrically assess assumptions necessary to prevent the surrogate paradox through hypothesis tests of stochastic dominance, monotonicity of regression functions, and non-negative residual treatment effects. More details are available in Hsiao et al 2025 (under review). A tutorial for this package can be found at <https://laylaparast.com/home/SurrogateParadoxTest.html>.

Emily Hsiao

SurrogateParadoxTest

Empirical Testing of Surrogate Paradox Assumptions

smoother_fitter function

<dl> <dt>X</dt>
<dd>Vector of X values</dd> <dt>Y</dt>
<dd>Vector of Y values</dd> <dt>kernel</dt>
<dd>Kernel to use in the kernel smoother; defaults to Gaussian kernel</dd> <dt>h</dt>
<dd>Bandwidth</dd></dl>

Arguments

Author

Helper function — smoother_fitter

<dl>

 <dt>X</dt>
<dd>Vector of X values</dd>

 <dt>Y</dt>
<dd>Vector of Y values</dd>

 <dt>kernel</dt>
<dd>Kernel to use in the kernel smoother; defaults to Gaussian kernel</dd>

 <dt>h</dt>
<dd>Bandwidth</dd>

</dl>

smoother_fitter: Helper function

Description

Usage

Value

Arguments

Author