ArticleJournal of applied statistics2021
A Multivariate Multiple Third-Variable Effect Analysis with an Application to Explore Racial and Ethnic Disparities in Obesity.
Article in Journal of applied statistics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- A cohort study of self-perception of ageing and all-cause mortality among older adults in China: a multiple mediators analysis.BMC public health · 2024Article
- Migrant status disparities in blood pressure: a multiple mediation analysis of modifiable factors.Journal of epidemiology and global health · 2023Article
- Do Adult Attachment Style or Personality Mediate the Relationship Between Childhood Maltreatment and Late-Life Depression in Poor Communities?Journal of geriatric psychiatry and neurology · 2023Article
- Associations of COVID-19 Hospitalizations, ICU Admissions, and Mortality with Black and White Race and Their Mediation by Air Pollution and Other Risk Factors in the Louisiana Industrial Corridor, March 2020-August 2021.International journal of environmental research and public health · 2023Article
- Bayesian mediation analysis methods to explore racial/ethnic disparities in anxiety among cancer survivors.Behaviormetrika · 2023Article
- Inference on moderation effect with third-variable effect analysis - application to explore the trend of racial disparity in oncotype dx test for breast cancer treatment.Journal of applied statistics · 2022Article
- Multilevel mediation analysis on time-to-event outcomes: Exploring racial/ethnic disparities in breast cancer survival in California.Research methods in medicine & health sciences · 2021Article
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Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Third-Variable effect refers to the intervening effect from a third variable (called mediators or confounders) to the observed relationship between an exposure and an outcome. The general multiple third-variable effect analysis method (TVEA) allows consideration of multiple mediators/confounders (MC) simultaneously and the use of linear and non-linear predictive models for estimating MC effects. Previous studies have found that compared with non-Hispanic White population, Blacks and Hispanic Whites suffered disproportionally more with obesity and related chronic diseases. In this paper, we extend the general TVEA to deal with multivariate/multicategorical predictors and multivariate response variables. We designed algorithms and an R package for this extension and applied MMA on the NHANES data to identify MCs and quantify the indirect effect of each MC in explaining both racial and ethnic disparities in obesity and the body mass index (BMI) simultaneously. We considered a number of socio-demographic variables, individual factors, and environmental variables as potential MCs and found that some of the ethnic/racial differences in obesity and BMI were explained by the included variables.
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Registered trials
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.