ArticleFrontiers in psychology2019
Bootstrap Model-Based Constrained Optimization Tests of Indirect Effects.
Article in Frontiers in psychology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
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Who cites it
5 citing papers in PubMed.
- Identifying potential drug targets for sepsis-related adult respiratory distress syndrome through comprehensive genetic analysis and druggability assessment.Journal of global health · 2025Article
- Proposal of an alternative way of reporting the results of comparative simulation studies.Frontiers in psychology · 2025Article
- Associations of Education Attainment With Postpartum Depression and the Mediating Exploration: A Mendelian Randomization Study.Depression and anxiety · 2025Article
- The relationship between emotional neglect and non-suicidal self-injury among middle school students in China: the mediating role of social anxiety symptoms and insomnia.BMC psychiatry · 2023Article
- Mediating effects of rumination and bedtime procrastination on the relationship between Internet addiction and poor sleep quality.Journal of behavioral addictions · 2020Article
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
In mediation analysis, conditions necessary for commonly recommended tests, including the confidence interval (CI)-based tests, to produce an accurate Type I error, do not generally hold for finite sample sizes and non-normally distributed model residuals. This is typically the case because of the complexity of testing a null hypothesis about indirect effects. To remedy these issues, we propose two extensions of the recently developed asymptotic Model-based Constrained Optimization (MBCO) likelihood ratio test (LRT), a promising new model comparison method for testing a general function of indirect effects. The proposed tests, semi-parametric and parametric bootstrap MBCO LRT are shown to yield a more accurate Type I error rate in smaller sample sizes and under various degrees of non-normality of the model residuals compared to the asymptotic MBCO LRT and the CI-based methods. We provide R script in the Supplemental Materials to perform all three MBCO LRTs.
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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.