mean_psi

<code>mean_psi</code> function for sample expectation of psi

Performs valid statistical inference on predicted data (IPD) using recent methods, where for a subset of the data, the outcomes have been predicted by an algorithm. Provides a wrapper function with specified defaults for the type of model and method to be used for estimation and inference. Further provides methods for tidying and summarizing results. Salerno et al., (2024) <doi:10.48550/arXiv.2410.09665>.

Stephen Salerno

Inference on Predicted Data

Jiacheng Miao

Awan Afiaz

Kentaro Hoffman

Anna Neufeld

Qiongshi Lu

Tyler H McCormick

Jeffrey T Leek

mean_psi function

<dl><dt>X</dt>
<dd>Array or data.frame containing covariates</dd>
<dt>Y</dt>
<dd>Array or data.frame of outcomes</dd>
<dt>theta</dt>
<dd>parameter theta</dd>
<dt>quant</dt>
<dd>quantile for quantile estimation</dd>
<dt>method</dt>
<dd>indicates the method to be used for M-estimation.
Options include "mean", "quantile", "ols", "logistic", and "poisson".</dd></dl>

Arguments

Sample expectation of psi — mean_psi

<dl>

<dt>X</dt>
<dd>Array or data.frame containing covariates</dd>


<dt>Y</dt>
<dd>Array or data.frame of outcomes</dd>


<dt>theta</dt>
<dd>parameter theta</dd>


<dt>quant</dt>
<dd>quantile for quantile estimation</dd>


<dt>method</dt>
<dd>indicates the method to be used for M-estimation.
Options include "mean", "quantile", "ols", "logistic", and "poisson".</dd>

</dl>

mean_psi: Sample expectation of psi

Description

Usage

Value

Arguments