adjust_coef

adjust_coef_with_continuous

Adjust an observed regression coefficient for a normally distributed
confounder

The strength of evidence provided by epidemiological and observational
studies is inherently limited by the potential for unmeasured confounding.
We focus on three key quantities: the observed bound of the confidence interval
closest to the null, a plausible residual effect size for an unmeasured continuous
or binary confounder, and a realistic mean difference or prevalence difference for
this hypothetical confounder. Building on the methods put forth by
Lin, Psaty, & Kronmal (1998) <doi:10.2307/2533848>, we can use these quantities to
assess how an unmeasured confounder may tip our result to insignificance, rendering the
study inconclusive.

Lucy D'Agostino McGowan

tipr

Tipping Point Analyses

adjust_coef function

<dl><dt>effect</dt>
<dd>Numeric. Observed exposure - outcome effect from a regression
model. This can be the beta coefficient, the lower confidence bound of
the beta coefficient, or the upper confidence bound of the beta
coefficient.</dd>
<dt>smd</dt>
<dd>Numeric. Estimated difference in scaled means between the
unmeasured confounder in the exposed population and unexposed population</dd>
<dt>outcome_association</dt>
<dd>Numeric. Estimated association
between the unmeasured confounder and the outcome.</dd>
<dt>verbose</dt>
<dd>Logical. Indicates whether to print informative message.
Default: <code>TRUE</code></dd></dl>

Arguments

Adjust an observed regression coefficient for a normally distributed
confounder — adjust_coef

<dl>

<dt>effect</dt>
<dd>Numeric. Observed exposure - outcome effect from a regression
model. This can be the beta coefficient, the lower confidence bound of
the beta coefficient, or the upper confidence bound of the beta
coefficient.</dd>


<dt>smd</dt>
<dd>Numeric. Estimated difference in scaled means between the
unmeasured confounder in the exposed population and unexposed population</dd>


<dt>outcome_association</dt>
<dd>Numeric. Estimated association
between the unmeasured confounder and the outcome.</dd>


<dt>verbose</dt>
<dd>Logical. Indicates whether to print informative message.
Default: <code>TRUE</code></dd>

</dl>

adjust_coef: Adjust an observed regression coefficient for a normally distributed confounder

Description

Usage

Value

Arguments

Examples