ArticlePloS one2020
A new linear regression-like residual for survival analysis, with application to genome wide association studies of time-to-event data.
Article in PloS one, 2020. 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.
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Who cites it
5 citing papers in PubMed.
- Gene x environment interaction analysis confirms genetic modifier effects on steroid efficacy via TGF-β pathway in Duchenne muscular dystrophy.European journal of human genetics : EJHG · 2026Article
- Is it time for genetic modifiers to predict prognosis in Duchenne muscular dystrophy?Nature reviews. Neurology · 2023Review
- A genome-wide association analysis of loss of ambulation in dystrophinopathy patients suggests multiple candidate modifiers of disease severity.European journal of human genetics : EJHG · 2023Article
- Improving efficiency of fitting Cox proportional hazards models for time-to-event outcomes in genome-wide association studies (GWAS).Bioinformatics advances · 2023Article
- The PPLD has advantages over conventional regression methods in application to moderately sized genome-wide association studies.PloS one · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
In linear regression, a residual measures how far a subject's observation is from expectation; in survival analysis, a subject's Martingale or deviance residual is sometimes interpreted similarly. Here we consider ways in which a linear regression-like interpretation is not appropriate for Martingale and deviance residuals, and we develop a novel time-to-event residual which does have a linear regression-like interpretation. We illustrate the utility of this new residual via simulation of a time-to-event genome-wide association study, motivated by a real study seeking genetic modifiers of Duchenne Muscular Dystrophy. By virtue of its linear regression-like characteristics, our new residual may prove useful in other contexts as well.
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Registered trials
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