Kern.FUN

Helper function; this calculates the kernel matrix

robust

internal

smooth

nonparametric

Estimates the proportion of treatment effect on a censored primary outcome that is explained by the treatment effect on a censored surrogate outcome/event. All methods are described in detail in Parast, et al (2020) "Assessing the Value of a Censored Surrogate Outcome" <doi:10.1007/s10985-019-09473-1> and Wang et al (2025) "Model-free Approach to Evaluate a Censored Intermediate Outcome as a Surrogate for Overall Survival" <doi:10.1002/sim.70268>. A tutorial for this package can be found at <https://www.laylaparast.com/surrogateoutcome>.

Layla Parast

SurrogateOutcome

Estimation of the Proportion of Treatment Effect Explained by
Surrogate Outcome Information

Xuan Wang

Kern.FUN function

<dl> <dt>zz</dt>
<dd>
zz</dd> <dt>zi</dt>
<dd>
zi</dd> <dt>bw</dt>
<dd>
bandwidth</dd> <dt>kern0</dt>
<dd>
kernel distribution</dd></dl>

Arguments

Layla Parast

Author


Calculates kernel matrix — Kern.FUN

<dl>

 <dt>zz</dt>
<dd>
zz</dd>

 <dt>zi</dt>
<dd>
zi</dd>

 <dt>bw</dt>
<dd>
bandwidth</dd>

 <dt>kern0</dt>
<dd>
kernel distribution</dd>

</dl>

Kern.FUN: Calculates kernel matrix

Description

Usage

Value

Arguments

Author