dat.scheidler

This meta-analysis serves as an example of meta-analyses of diagnostic tests.

dataset

Provides alternative statistical methods for meta-analysis, including:
- bivariate generalized linear mixed models for synthesizing odds ratios, relative risks,
and risk differences
(Chu et al., 2012 <doi:10.1177/0962280210393712>)
- heterogeneity tests and measures and penalization methods that are robust to outliers
(Lin et al., 2017 <doi:10.1111/biom.12543>;
Wang et al., 2022 <doi:10.1002/sim.9261>);
- measures, tests, and visualization tools for publication bias or small-study effects
(Lin and Chu, 2018 <doi:10.1111/biom.12817>;
Lin, 2019 <doi:10.1002/jrsm.1340>;
Lin, 2020 <doi:10.1177/0962280220910172>;
Shi et al., 2020 <doi:10.1002/jrsm.1415>);
- meta-analysis of combining standardized mean differences and odds ratios
(Jing et al., 2023 <doi:10.1080/10543406.2022.2105345>);
- meta-analysis of diagnostic tests for synthesizing sensitivities, specificities, etc.
(Reitsma et al., 2005 <doi:10.1016/j.jclinepi.2005.02.022>;
Chu and Cole, 2006 <doi:10.1016/j.jclinepi.2006.06.011>);
- meta-analysis methods for synthesizing proportions
(Lin and Chu, 2020 <doi:10.1097/ede.0000000000001232>);
- models for multivariate meta-analysis, measures of inconsistency degrees of freedom
in Bayesian network meta-analysis, and predictive P-score
(Lin and Chu, 2018 <doi:10.1002/jrsm.1293>;
Lin, 2020 <doi:10.1080/10543406.2020.1852247>;
Rosenberger et al., 2021 <doi:10.1186/s12874-021-01397-5>).

Lifeng Lin

altmeta

Alternative Meta-Analysis Methods

Yaqi Jing

Kristine J. Rosenberger

Linyu Shi

Yipeng Wang

Haitao Chu

dat.scheidler function

A data frame with 44 studies with the following 5 variables; each row represents a study.<dl>
 <dt><code>dt</code></dt>
<dd>types of diagnostic tests; CT: computed tomography; LAG: lymphangiography; and MRI: magnetic resonance imaging.</dd> <dt><code>tp</code></dt>
<dd>counts of true positives.</dd> <dt><code>fp</code></dt>
<dd>counts of false positives.</dd> <dt><code>fn</code></dt>
<dd>counts of false negatives.</dd> <dt><code>tn</code></dt>
<dd>counts of true negatives.</dd> 
</dl>

Format

Meta-Analysis on the Utility of Lymphangiography, Computed Tomography, and Magnetic Resonance Imaging for the Diagnosis of Lymph Node Metastasis — dat.scheidler

A data frame with 44 studies with the following 5 variables; each row represents a study.<dl>
 <dt><code>dt</code></dt>
<dd>types of diagnostic tests; CT: computed tomography; LAG: lymphangiography; and MRI: magnetic resonance imaging.</dd>

 <dt><code>tp</code></dt>
<dd>counts of true positives.</dd>

 <dt><code>fp</code></dt>
<dd>counts of false positives.</dd>

 <dt><code>fn</code></dt>
<dd>counts of false negatives.</dd>

 <dt><code>tn</code></dt>
<dd>counts of true negatives.</dd>

 
</dl>

dat.scheidler: Meta-Analysis on the Utility of Lymphangiography, Computed Tomography, and Magnetic Resonance Imaging for the Diagnosis of Lymph Node Metastasis

Description

Usage

Arguments

Format