Evidence map›Paper›PMID 19336261›Full record

ArticleContemporary clinical trials2009

A non-inferiority test of areas under two parametric ROC curves.

Hua Jin, Ying Lu

Abstract read
In one paragraph

Article in Contemporary clinical trials, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hua JinSchool of Mathematical Sciences and Center for Studies of Psychological Application, South China Normal University, Guangzhou, China. jinh1@163.com
Ying Lu

Funding

Statistical Methods for Evaluation and Validation of Diagnostic TestsR01EB004079 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LU, YING · 2006 to 2008
$684k
Statistical methods for utility of multiple testsR03AR047104 · NIAMS · UNIVERSITY OF CALIFORNIA SAN FRANCISCO · PI LU, YING · 2001 to 2003
$221k
NIAMS NIH HHS R03 AR047104NIAMS NIH HHS R03 AR47104NIBIB NIH HHS R01 EB004079NIBIB NIH HHS R01EB004079
6 · The paper itself

Abstract

Equivalence or non-inferiority in diagnostic accuracy of two medical diagnostic tests is a common medical problem. Statistical tests of non-inferiority of diagnostic tests have long been a subject of interest in medicine and biostatistical research. Accuracy of a continuous diagnostic test can be evaluated by the area under a receiver operating characteristic (ROC) curve. A conventional non-inferiority test for areas of two parametric ROC curves has been proposed by Zhou, Obuchowski, and McClish [Zhou XH, Obuchowski NA, McClish DK. Statistical Methods in Diagnostic Medicine. New York: John Wiley; 2002]. In this paper, we showed that this conventional approach is anti-conservative and proposed a new statistical test based on restricted maximum likelihood estimator to achieve designed type I error rate. Simulation studies supported this new test to be appropriate for small sample size or highly correlated diagnostic modalities.

Indexed as

DiagnosisROC CurveHumansModels, StatisticalSample Size

Identifiers

PMID19336261
PMCPMC11948746

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.