compute_risk

Calculates the cross-validated risk for the optimal bandwidth selection in
kernel smoothing approach.

internal

Provides a framework for estimating causal effects of a continuous
exposure using observational data, and implementing matching and weighting
on the generalized propensity score.
Wu, X., Mealli, F., Kioumourtzoglou, M.A., Dominici, F. and Braun, D., 2022.
Matching on generalized propensity scores with continuous exposures. Journal
of the American Statistical Association, pp.1-29.

Naeem Khoshnevis

CausalGPS

Matching on Generalized Propensity Scores with Continuous
Exposures

Xiao Wu

Danielle Braun

compute_risk function

<dl><dt>h</dt>
<dd>A scalar representing the bandwidth value.</dd>
<dt>matched_Y</dt>
<dd>A vector of outcome variable in the matched set.</dd>
<dt>matched_w</dt>
<dd>A vector of continuous exposure variable in the matched set.</dd>
<dt>matched_cw</dt>
<dd>A vector of counter or weight variable in the matched set.</dd>
<dt>w_vals</dt>
<dd>A vector of values that you want to calculate the values of
the ERF at.</dd>
<dt>kernel_appr</dt>
<dd>Internal kernel approach. Available options are <code>locpol</code>
and <code>kernsmooth</code>.</dd></dl>

Arguments

Compute risk value — compute_risk

<dl>

<dt>h</dt>
<dd>A scalar representing the bandwidth value.</dd>


<dt>matched_Y</dt>
<dd>A vector of outcome variable in the matched set.</dd>


<dt>matched_w</dt>
<dd>A vector of continuous exposure variable in the matched set.</dd>


<dt>matched_cw</dt>
<dd>A vector of counter or weight variable in the matched set.</dd>


<dt>w_vals</dt>
<dd>A vector of values that you want to calculate the values of
the ERF at.</dd>


<dt>kernel_appr</dt>
<dd>Internal kernel approach. Available options are <code>locpol</code>
and <code>kernsmooth</code>.</dd>

</dl>

compute_risk: Compute risk value

Description

Usage

Value

Arguments