ArticleStatistics in biopharmaceutical research2021
Partial correlation coefficient for a study with repeated measurements.
Article in Statistics in biopharmaceutical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Phase-resolved functional lung MRI detects single-dose and sustained bronchodilator responses in COPD in a randomized crossover trial.European radiology · 2026Trial
- When normalization induces correlation: shared and unstable references can create hidden dependencies.NPJ systems biology and applications · 2026Article
- Longitudinal White Matter Maturation in Preterm Infants: Functional Pathway-Specific Trajectories and Associations with Motor Outcomes.Journal of clinical medicine · 2026Article
- Image complexity-based fMRI-BOLD visual network categorization across visual datasets using topological descriptors and deep-hybrid learning.Scientific reports · 2025Article
- Development of Transferable Coarse-Grained Lipid Models with Optimized Structural and Elastic Membrane Properties.Journal of chemical theory and computation · 2025Article
- Article
- Conservative confidence intervals for the intraclass correlation coefficient for clustered binary data.Journal of applied statistics · 2022Article
- Optimal two-stage designs based on restricted mean survival time for a single-arm study.Contemporary clinical trials communications · 2021Article
- Machine learning methods to predict amyloid positivity using domain scores from cognitive tests.Scientific reports · 2021Article
- Partial correlation coefficient for a study with repeated measurements.Statistics in biopharmaceutical research · 2021Article
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Authors and funding
6 authors.
Funding
Abstract
Repeated data are increasingly collected in studies to investigate the trajectory of change in measurements over time. Determining a link between one repeated measurement with another that is considered as the biomarker for disease progression, may provide a new target for drug development. When a third variable is associated with one of the two measurements, partial correlation after eliminating the effect of that variable is able to provide reliable estimate for association as compared to the existing raw correlation for repeated data. We propose using linear regression models to compute residuals by modeling a relationship between each measurement and a third variable. The computed residuals are then used in a linear mixed model (implemented by SAS Proc Mixed) to compute partial correlation for repeated data. Alternatively, the partial correlation may be computed as the average of partial correlations at each visit. We provide two real examples to illustrate the application of the proposed partial correlation, and conduct extensive numerical studies to compare the proposed partial correlation coefficients.
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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.