Evidence map›Paper›PMID 27858965›Full record

ArticleBiometrics2017

Model-robust inference for continuous threshold regression models.

Youyi Fong, Chongzhi Di, Ying Huang, Peter B Gilbert

Abstract read
In one paragraph

Article in Biometrics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Temperature thresholds induce abrupt shifts in biodiversity and ecosystem services in montane ecosystems worldwide.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Blood biomarkers differentiate AD-related versus non-AD-related cognitive deficits.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Threshold-based subgroup testing in logistic regression models in two-phase sampling designs.Journal of the Royal Statistical Society. Series C, Applied statistics · 2021
    Article
  12. Article
  13. Article
  14. Fast Bootstrap Confidence Intervals for Continuous Threshold Linear Regression.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2019
    Article
  15. Article
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.

Youyi FongFred Hutchinson Cancer Research Center, Seattle Washington 98109, U.S.A.
Chongzhi DiFred Hutchinson Cancer Research Center, Seattle Washington 98109, U.S.A.
Ying HuangFred Hutchinson Cancer Research Center, Seattle Washington 98109, U.S.A.
Peter B GilbertFred Hutchinson Cancer Research Center, Seattle Washington 98109, U.S.A.

Funding

SDMC: HIV Vaccine Trials NetworkUM1AI068635 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Peter B. Gilbert, Yunda Huang · 2011 to 2026
$385.9M
Statistical Methods in HIV Vaccine Efficacy TrialsR37AI054165 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Peter B. Gilbert · 2010 to 2026
$6.7M
Statistical Methods for Selection and Evaluation of BiomarkersR01GM106177 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI HUANG, YING · 2013 to 2018
$1.6M
Statistical methods for HIV-1 immune correlates studiesR01AI122991 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI FONG, YOUYI · 2016 to 2020
$1.6M
FHCRC High-Performance Computing ClusterS10OD020069 · OD · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPERBERG, CHARLES L · 2015 to 2015
$600k
Statistical methods for GxE interactions: Measurement error & time varying exposuR21ES022332 · NIEHS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI DI, CHONGZHI · 2013 to 2014
$481k
NIAID NIH HHS R01 AI122991NIAID NIH HHS R37 AI054165NIAID NIH HHS UM1 AI068635NIEHS NIH HHS R21 ES022332NIGMS NIH HHS R01 GM106177NIH HHS S10 OD020069
6 · The paper itself

Abstract

We study threshold regression models that allow the relationship between the outcome and a covariate of interest to change across a threshold value in the covariate. In particular, we focus on continuous threshold models, which experience no jump at the threshold. Continuous threshold regression functions can provide a useful summary of the association between outcome and the covariate of interest, because they offer a balance between flexibility and simplicity. Motivated by collaborative works in studying immune response biomarkers of transmission of infectious diseases, we study estimation of continuous threshold models in this article with particular attention to inference under model misspecification. We derive the limiting distribution of the maximum likelihood estimator, and propose both Wald and test-inversion confidence intervals. We evaluate finite sample performance of our methods, compare them with bootstrap confidence intervals, and provide guidelines for practitioners to choose the most appropriate method in real data analysis. We illustrate the application of our methods with examples from the HIV-1 immune correlates studies.

Indexed as

Models, StatisticalHIV-1HumansLikelihood FunctionsMother-to-child transmission of HIV-1Profile likelihood ratio under model misspecificationRegression kinkRV144 immune correlates studies

Identifiers

PMID27858965
PMCPMC5435560

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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.