adjust_emc

<a href="https://lifecycle.r-lib.org/articles/stages.html#deprecated"><img src="figures/lifecycle-deprecated.svg?package=multibias&version=1.6.3" alt="[Deprecated]"></a>
<code>adjust_emc()</code> was renamed to <code>adjust_em()</code>

internal

Quantify the causal effect of a binary exposure on a binary
outcome with adjustment for multiple biases. The functions can
simultaneously adjust for any combination of uncontrolled confounding,
exposure/outcome misclassification, and selection bias.
The underlying method generalizes the concept of combining inverse
probability of selection weighting with predictive value weighting.
Simultaneous multi-bias analysis can be used to enhance the validity
and transparency of real-world evidence obtained from observational,
longitudinal studies. Based on the work from Paul Brendel, Aracelis Torres,
and Onyebuchi Arah (2023) <doi:10.1093/ije/dyad001>.

Paul Brendel

multibias

Simultaneous Multi-Bias Adjustment

adjust_emc function

<a href='https://lifecycle.r-lib.org/articles/stages.html#deprecated'><img src='figures/lifecycle-deprecated.svg' alt='[Deprecated]' /></a>
<code>adjust_emc()</code> was renamed to <code>adjust_em()</code>

adjust_emc: Adust for exposure misclassification.

Description

Usage

Arguments