Statistical Modeling of Discrete Percentage Measurements With Application to Construction of Acceptance Bounds for Wood Failure in Structural Adhesive Testing

Peer reviewed: 
Yes, item is peer reviewed.
Scholarly level: 
Faculty/Staff
Final version published as: 

Loughin, T. M., Payne, N., Casilla, R., and Lum, C., "Statistical Modeling of Discrete Percentage Measurements With Application to Construction of Acceptance Bounds for Wood Failure in Structural Adhesive Testing," Journal of Testing and Evaluation 45(5), https://doi.org/10.1520/JTE20150189 Published by ASTM.

Date created: 
2016
Identifier: 
DOI: 10.1520/JTE20150189
Keywords: 
Binomial
Random effects
Laboratories
Overdispersion
Wood
Adhesive
Abstract: 

The goals of this paper are:

(1) to provide a statistical analysis approach that is appropriate for data from an interlaboratory study where responses are measured in discrete percentages and are subject to multiple sources of random variability, and (2) to apply this model to data on wood-failure percentages from block-shear tests on structural wood adhesives.

We treat percentage responses measured in 5-point intervals as having arisen from observing 20 independent binary responses on different parts of the observed wood blocks. The overdispersion that is likely to result from the practical inadequacy of this assumption is overcome empirically by the inclusion of a random effect for blocks. We propose an analysis based on a parametric bootstrap to provide sampling distributions for statistics that regulators might wish to use in setting standards for acceptance of wood adhesives. Similar computational methods are developed to assess the fit of the model. This model is shown to provide a reasonably good fit or actual data in many of the cases to which it was applied.

Language: 
English
Document type: 
Article
Rights: 
Rights remain with the authors. ASTM Copyright Transfer Agreement allows for the use of the publisher version 12 months after publication.
File(s): 
Sponsor(s): 
National Science and Engineering Research Council of Canada (NSERC)
Statistics: