Continuous Ordinal Regression for Analysis of Visual Analogue Scales: The R Package ordinalCont

Dublin Core

Title

Continuous Ordinal Regression for Analysis of Visual Analogue Scales: The R Package ordinalCont

Subject

Continuous Ordinal Regression for Analysis of Visual Analogue Scales: The R Package ordinalCont

Description

This paper introduces the R package ordinalCont, which implements an ordinal regression framework for response variables which are recorded on a visual analogue scale
(VAS). This scale is used when recording subjects’ perception of an intangible quantity
such as pain, anxiety or quality of life, and consists of a mark made on a linear scale.
We implement continuous ordinal regression models for VAS as the appropriate method
of analysis for such responses, and introduce smoothing terms and random effects in the
linear predictor. The model parameters are estimated using constrained optimization of
the penalized likelihood and the penalty parameters are automatically selected via maximization of their marginal likelihood. The estimation algorithm is shown to perform
well, in a simulation study. Two examples of application are given: the first involves the
analysis of pain outcomes in a clinical trial for laser treatment for chronic neck pain; the
second is an analysis of quality of life outcomes in a clinical trial for chemotherapy for the
treatment of breast cancer.

Creator

Maurizio Manuguerra

Source

https://www.jstatsoft.org/article/view/v096i08

Publisher

Macquarie University

Date

November 2020

Contributor

Fajar bagus W

Format

PDF

Language

Inggris

Type

Text

Files

Citation

Maurizio Manuguerra, “Continuous Ordinal Regression for Analysis of Visual Analogue Scales: The R Package ordinalCont,” Repository Horizon University Indonesia, accessed February 17, 2025, https://repository.horizon.ac.id/items/show/8174.