acc_dg2

Perform PVB correction by Begg and Greenes' method 2 as described in deGroot et al (2011),
 in which it also includes PPV and NPV calculation. This is limited to only one covariate.

Performs partial verification bias (PVB) correction for binary
diagnostic tests, where PVB arises from selective patient verification in
diagnostic accuracy studies. Supports correction of important accuracy
measures -- sensitivity, specificity, positive predictive values and
negative predictive value -- under missing-at-random and
missing-not-at-random missing data mechanisms. Available methods and
references are "Begg and Greenes' methods" in Alonzo & Pepe (2005)
<doi:10.1111/j.1467-9876.2005.00477.x> and deGroot et al. (2011)
<doi:10.1016/j.annepidem.2010.10.004>; "Multiple imputation" in
Harel & Zhou (2006) <doi:10.1002/sim.2494>, "EM-based logistic regression"
in Kosinski & Barnhart (2003) <doi:10.1111/1541-0420.00019>;
"Inverse probability weighting" in Alonzo & Pepe (2005)
<doi:10.1111/j.1467-9876.2005.00477.x>; "Inverse probability bootstrap
sampling" in Nahorniak et al. (2015) <doi:10.1371/journal.pone.0131765>
and Arifin & Yusof (2022) <doi:10.3390/diagnostics12112839>;
"Scaled inverse probability resampling methods" in Arifin & Yusof (2025)
<doi:10.1371/journal.pone.0321440>.

Wan Nor Arifin

PVBcorrect

Partial Verification Bias Correction for Diagnostic Accuracy

acc_dg2 function

<dl><dt>data</dt>
<dd>A data frame, with at least "Test" and "Disease" variables.</dd>
<dt>test</dt>
<dd>The "Test" variable name, i.e. the test result. The variable must be in binary; positive = 1, negative = 0 format.</dd>
<dt>disease</dt>
<dd>The "Disease" variable name, i.e. the true disease status. The variable must be in binary; positive = 1, negative = 0 format.</dd>
<dt>covariate</dt>
<dd>The name(s) of covariate(s), i.e. other variables associated with either test or disease status.
Specify as name vector, e.g. c("X1", "X2") for two or more variables. The variables must be in formats acceptable to GLM.</dd>
<dt>description</dt>
<dd>Print the name of this analysis. The default is <code>TRUE</code>. This can be turned off for repeated analysis, for example in bootstrapped results.</dd></dl>

Arguments

PVB correction by Begg and Greenes' method 2 (deGroot et al, one covariate) — acc_dg2

<dl>

<dt>data</dt>
<dd>A data frame, with at least "Test" and "Disease" variables.</dd>


<dt>test</dt>
<dd>The "Test" variable name, i.e. the test result. The variable must be in binary; positive = 1, negative = 0 format.</dd>


<dt>disease</dt>
<dd>The "Disease" variable name, i.e. the true disease status. The variable must be in binary; positive = 1, negative = 0 format.</dd>


<dt>covariate</dt>
<dd>The name(s) of covariate(s), i.e. other variables associated with either test or disease status.
Specify as name vector, e.g. c("X1", "X2") for two or more variables. The variables must be in formats acceptable to GLM.</dd>


<dt>description</dt>
<dd>Print the name of this analysis. The default is <code>TRUE</code>. This can be turned off for repeated analysis, for example in bootstrapped results.</dd>

</dl>

acc_dg2: PVB correction by Begg and Greenes' method 2 (deGroot et al, one covariate)

Description

Usage

Value

Arguments

References

Examples