Evidence map›Paper›PMID 34176951›Full record

ArticleBiometrika2020

On specification tests for composite likelihood inference.

Jing Huang, Yang Ning, Nancy Reid, Yong Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biometrika, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

4 authors.

Jing HuangDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, U.S.A.
Yang NingDepartment of Statistics and Data Science, Cornell University, Comstock Hall 1188, Ithaca, New York 14853, U.S.A.
Nancy ReidDepartment of Statistical Sciences, University of Toronto, Toronto M5S 3GS, Canada.
Yong ChenDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, U.S.A.

Funding

Characterizing Disease Trajectory for Improving Treatment in Pediatric Crohn's DiseaseR01HD099348 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI HUANG, JING · 2019 to 2023
$3.2M
NICHD NIH HHS R01 HD099348
6 · The paper itself

Abstract

Composite likelihood functions are often used for inference in applications where the data have a complex structure. While inference based on the composite likelihood can be more robust than inference based on the full likelihood, the inference is not valid if the associated conditional or marginal models are misspecified. In this paper, we propose a general class of specification tests for composite likelihood inference. The test statistics are motivated by the fact that the second Bartlett identity holds for each component of the composite likelihood function when these components are correctly specified. We construct the test statistics based on the discrepancy between the so-called composite information matrix and the sensitivity matrix. As an illustration, we study three important cases of the proposed tests and establish their limiting distributions under both null and local alternative hypotheses. Finally, we evaluate the finite-sample performance of the proposed tests in several examples.

Indexed as

Bartlett identityInformation matrixMisspecification testModel specification

Identifiers

PMID34176951
PMCPMC8232013

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.