Analysis of robust design experiments with time-dependent ordinal response characteristics: a quality improvement study from the horticulture industry

DOI10.1080/02664760802566796OpenAlexW2058272248MaRDI QIDQ5123398

Rodney N. Edmondson, Nick R. Parsons, Steven G. Gilmour

Publication date: 28 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760802566796

zbMATH Keywords

proportional odds modeltwo-stage analysisrobust product designjoint mean-dispersion modelordinal scores

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R
• repolr
• bootstrap

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Longitudinal data analysis using generalized linear models
• Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R
• Bayesian Analysis of Ordered Categorical Data from Industrial Experiments
• The Design and Analysis of 2 k-p × s Prototype Experiments
• An extended quasi-likelihood function
• Performance Measures Independent of Adjustment: An Explanation and Extension of Taguchi's Signal-to-Noise Ratios
• The Measurement of Observer Agreement for Categorical Data
• Analysis of dynamic robust design experiments
• Presentation of Ordinal Regression Analysis on the Original Scale
• Generalized linear models for the analysis of quality-improvement experiments
• Signal-to-Noise Ratios, Performance Criteria, and Transformations
• A Generalized Estimating Equation Method for Fitting Autocorrelated Ordinal Score Data with an Application in Horticultural Research

This page was built for publication: Analysis of robust design experiments with time-dependent ordinal response characteristics: a quality improvement study from the horticulture industry