print.episensr.booted

Print bootstrap-ed confidence intervals for selection and misclassification bias functions.

Basic sensitivity analysis of the observed relative risks adjusting
for unmeasured confounding and misclassification of the
exposure/outcome, or both. It follows the bias analysis methods and
examples from the book by Lash T.L, Fox M.P, and Fink A.K.
"Applying Quantitative Bias Analysis to Epidemiologic Data",
('Springer', 2021).

Denis Haine

episensr

Basic Sensitivity Analysis of Epidemiological Results

print.episensr.booted function

<dl><dt>x</dt>
<dd>An object of class 'episensr.booted'.</dd>
<dt>digits</dt>
<dd>Minimal number of _significant_ digits, see 'print.default'.</dd>
<dt>...</dt>
<dd>Other unused arguments.</dd></dl>

Arguments

Print bootstrapped confidence intervals — print.episensr.booted

<dl>

<dt>x</dt>
<dd>An object of class 'episensr.booted'.</dd>


<dt>digits</dt>
<dd>Minimal number of _significant_ digits, see 'print.default'.</dd>


<dt>...</dt>
<dd>Other unused arguments.</dd>

</dl>

print.episensr.booted: Print bootstrapped confidence intervals

Description

Usage

Value

Arguments