trim_pr

Trimming the estimates to be strictly between 0 and 1

Estimation and inference methods for causal relative and attributable risk in case-control and case-population studies
under the monotone treatment response and monotone treatment selection assumptions.
For more details, see the paper by Jun and Lee (2023),
"Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions," <arXiv:2004.08318 [econ.EM]>,
accepted for publication in Journal of Business & Economic Statistics.

Sokbae Lee

ciccr

Causal Inference in Case-Control and Case-Population Studies

Sung Jae Jun

trim_pr function

<dl><dt>ps</dt>
<dd>n-dimensional vector of estimated probabilities</dd>
<dt>eps</dt>
<dd>a small constant that determines the trimming of the estimated probabilities.
Specifically, the estimate probability is trimmed to be between eps and 1-eps (default = 1e-8).</dd></dl>

Arguments

Trimming the estimates to be strictly between 0 and 1 — trim_pr

<dl>

<dt>ps</dt>
<dd>n-dimensional vector of estimated probabilities</dd>


<dt>eps</dt>
<dd>a small constant that determines the trimming of the estimated probabilities.
Specifically, the estimate probability is trimmed to be between eps and 1-eps (default = 1e-8).</dd>

</dl>

trim_pr: Trimming the estimates to be strictly between 0 and 1

Description

Usage

Value

Arguments