ArticleBiometrics2018
Reader Reaction: A note on testing and estimation in marker-set association study using semiparametric quantile regression kernel machine.
Article in Biometrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Testing microbiome association using integrated quantile regression models.Bioinformatics (Oxford, England) · 2022Article
- Robust kernel association testing (RobKAT).Genetic epidemiology · 2020Article
- Rejoinder to "A note on testing and estimation in marker-set association study using semiparametric quantile regression kernel machine".Biometrics · 2018Article
Corrections and comments
- Commented on by
- Comment on
Authors and funding
2 authors.
Funding
Abstract
Kong et al. (2016, Biometrics 72, 364-371) presented a quantile regression kernel machine (QRKM) test for robust analysis of genetic marker-set association studies. A potential limitation of QRKM is the permutation-based test design may be unscalable for the massive sizes of modern datasets. In this article, we present an alternative strategy for p-value calculation of QRKM, which is capable of speeding up the QRKM testing procedure dramatically while maintaining the same testing performance as QRKM. The effectiveness of our approach is demonstrated via simulation studies.
Indexed as
Identifiers
What OpenQuestion holds
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.