Extracting Scalar Measures from Curves

Fuente: arXiv
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Auteurs principaux: Yao, Lanqiu, Tarpey, Thaddeus
Format: Preprint
Publié: 2024
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author Yao, Lanqiu
Tarpey, Thaddeus
author_facet Yao, Lanqiu
Tarpey, Thaddeus
contents The ability to order outcomes is necessary to make comparisons which is complicated when there is no natural ordering on the space of outcomes, as in the case of functional outcomes. This paper examines methods for extracting a scalar summary from functional or longitudinal outcomes based on an average rate of change which can be used to compare curves. Common approaches used in practice use a change score or an analysis of covariance (ANCOVA) to make comparisons. However, these standard approaches only use a fraction of the available data and are inefficient. We derive measures of performance of an averaged rate of change of a functional outcome and compare this measure to standard measures. Simulations and data from a depression clinical trial are used to illustrate results.
format Preprint
id arxiv_https___arxiv_org_abs_2402_01827
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Extracting Scalar Measures from Curves
Yao, Lanqiu
Tarpey, Thaddeus
Methodology
The ability to order outcomes is necessary to make comparisons which is complicated when there is no natural ordering on the space of outcomes, as in the case of functional outcomes. This paper examines methods for extracting a scalar summary from functional or longitudinal outcomes based on an average rate of change which can be used to compare curves. Common approaches used in practice use a change score or an analysis of covariance (ANCOVA) to make comparisons. However, these standard approaches only use a fraction of the available data and are inefficient. We derive measures of performance of an averaged rate of change of a functional outcome and compare this measure to standard measures. Simulations and data from a depression clinical trial are used to illustrate results.
title Extracting Scalar Measures from Curves
topic Methodology
url https://arxiv.org/abs/2402.01827