Evidence map›Paper›PMID 37009591›Full record

ArticleJournal of applied statistics2023

Homogeneity test of relative risk ratios for stratified bilateral data under different algorithms.

Ke-Yi Mou, Chang-Xing Ma, Zhi-Ming Li

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In one paragraph

Article in Journal of applied statistics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Ke-Yi MouCollege of Mathematics and System Science, Xinjiang University, Urumqi, People's Republic of China.ORCID https://orcid.org/0000-0001-5202-5128
Chang-Xing MaDepartment of Biostatistics, University at Buffalo, Buffalo, NY, USA.ORCID https://orcid.org/0000-0002-4696-2008
Zhi-Ming LiCollege of Mathematics and System Science, Xinjiang University, Urumqi, People's Republic of China.ORCID https://orcid.org/0000-0002-6570-6325

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical clinical studies about paired body parts often involve stratified bilateral data. The correlation between responses from paired parts should be taken into account to avoid biased or misleading results. This paper aims to test if the relative risk ratios across strata are equal under the optimal algorithms. Based on different algorithms, we obtain the desired global and constrained maximum likelihood estimations (MLEs). Three asymptotic test statistics (i.e.

Indexed as

algorithmasymptotic testBilateral dataDonner's modelpowerType I error rate

Identifiers

PMID37009591
PMCPMC10062238

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Registered trials

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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.