ArticleData in brief2024
A refined spirometry dataset for comparing segmented (piecewise) linear models to that of GAMLSS.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The predicted body weight equation overestimates lung sizes of female, critically ill patients: an analysis of randomized, controlled trials and real-world clinical data.Intensive care medicine · 2026Article
- Biomechanical Phenotyping of Forced Expiration for Precision Pulmonary Rehabilitation: A Machine Learning Approach to Identify Structural and Kinetic Drivers.Advances in respiratory medicine · 2026Article
- A refined spirometry dataset for comparing segmented (piecewise) linear models to that of GAMLSS.Data in brief · 2024Article
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1 author.
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Abstract
Generalized Additive Models for Location, Scale, and Shape (GAMLSS) are widely used for developing spirometric reference equations but are often complex, requiring additional spline tables. This study explores the potential of Segmented (piecewise) Linear Regression as an alternative, comparing its predictive accuracy to GAMLSS and examining the agreement between the two methods. Spirometry data from nearly 16,600 patients, deemed Grade "A" and "B" acceptable from the NHANES 2007-2012 dataset, was analyzed. The dataset includes both nominal and scalar variables. Reference equations for forced expiratory volume in 1 s (FEV
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