
  Data from Nishimura (2007) of anti-cyclic citrullinated peptide antibody (anti-CCP) which report the four frequencies of the classification outcomes.


datasets

This package allows doing meta-analysis for primary studies with classification outcomes in order to evaluate systematically the accuracies of classifiers, namely, the diagnostic tests. It provides functions to fit the bivariate model of Reitsma et al.(2005). Moreover, if the reference employed in the classification process isn't a gold standard, its deficit can be detected and its influence to the underestimation of the diagnostic test's accuracy can be corrected, as described in Botella et al.(2013).

Huiling Huang

Metatron

Meta-analysis for Classification Data and Correction to
Imperfect Reference

ccp function

A data frame containing 7 variables and 37 observations. The variables are:
<table><tr><td>
 test </td>
<td> <code>factor</code> </td>
</tr><tr><td> name of the screening test </td>
<td> 
 study_id </td>
</tr><tr><td> <code>factor</code> </td>
<td> primary study name </td>
</tr><tr><td>
 generation </td>
<td> <code>factor</code> </td>
</tr><tr><td> CCP generation used in the study, can be used as covariate. </td>
<td>
 TP </td>
</tr><tr><td> <code>numeric</code> </td>
<td> number of true positives </td>
</tr><tr><td>
 FN </td>
<td> <code>numeric</code> </td>
</tr><tr><td> number of false negatives </td>
<td>
 FP </td>
</tr><tr><td> <code>numeric</code> </td>
<td> number of false positives </td>
</tr></table>

Format

Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy, Chapter 10

ccp: Anti-cyclic Citrullinated Peptide Antibody

Description

Usage

Arguments

Format

Source

References

test	`factor`
name of the screening test	study_id
`factor`	primary study name
generation	`factor`
CCP generation used in the study, can be used as covariate.	TP
`numeric`	number of true positives
FN	`numeric`
number of false negatives	FP
`numeric`	number of false positives