ArticleStatistical methods in medical research2018
Conditional independence test by generalized Kendall's tau with generalized odds ratio.
Article in Statistical methods in medical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Simulating metabolic pathways to enhance interpretations of metabolome genome-wide association studies.Scientific reports · 2025Article
- A double-robust test for high-dimensional gene coexpression networks conditioning on clinical information.Biometrics · 2023Article
- Conditional Independence Test of Failure and Truncation Times: Essential Tool for Method Selection.Computational statistics & data analysis · 2022Article
- Concurrent validity and intrarater reliability of two ultrasound-based methods for assessing patellar tendon stiffness.Ultrasound (Leeds, England) · 2022Article
- A flexible and robust method for assessing conditional association and conditional concordance.Statistics in medicine · 2019Article
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Authors and funding
4 authors.
Funding
Abstract
Determining conditional dependence is a challenging but important task in both model building and in applications such as genetic association studies and graphical models. Research on this topic has focused on kernel-based methods or has used categorical conditioning variables because of the challenge of the curse of dimensionality. To overcome this challenge, we propose a class of tests for conditional independence without any restriction on the distribution of the conditioning variables. The proposed test statistic can be treated as a generalized weighted Kendall's tau, in which the generalized odds ratio is utilized as a weight function to account for the distance between different values of the conditioning variables. The test procedure has desirable asymptotic properties and is easy to implement. We evaluate the finite sample performance of the proposed test through simulation studies and illustrate it using two real data examples.
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