Showing papers by "Per B. Brockhoff published in 2015"
TL;DR: An approach for automated mixed ANOVA/ANCOVA modeling together with the open source R package lmerTest developed by the authors that can perform automated complex mixed-effects modeling is introduced.
93 citations
TL;DR: Consumer liking was assessed for streaky bacon and pork belly roll from entire male pigs with an androstenone (AND) content and a skatole (SKA) content, and a sensory profile analysis showed that AND increased the boar taint of bacon, while both AND and SKA increased the Boar Taint of the pork bellyroll.
26 citations
TL;DR: In this article, a mixed model ANOVA analysis approach, the Mixed Assessor Model (MAM), was proposed to take the scale range differences between individual assessors into account by a simple inclusion of the product averages as a covariate in the modeling.
22 citations
TL;DR: The QSAR model, developed for permeation enhancement, is a valuable in silico approach for both screening of new permeation enhancers and physicochemical optimisation of surfactant enhancer systems.
21 citations
01 Jan 2015
TL;DR: An approach for automated mixed ANOVA/ANCOVA modeling together with the open source R package lmerTest developed by the authors that can perform automated complex mixed-effects modeling is introduced and the benefits are illustrated on four data sets coming from consumer/sensory studies.
Abstract: Mixed effects models have become increasingly prominent in sensory and consumer science. Still applying such models may be challenging for a sensory practitioner due the challenges associated with the choosing the random effects, selecting an appropriate model, interpreting the results. In this paper we introduce an approach for automated mixed ANOVA/ANCOVA modeling together with the open source R package lmerTest developed by the authors that can perform automated complex mixed-effects modeling. The package can in an automated way investigate and incorporate the necessary random-effects by sequentially removing non-significant random terms in the mixed model, and similarly test and remove fixed effects. Tables and figures provide an overview of the structure and present post hoc analysis. With this approach, complex error structures can be investigated, identified and incorporated whenever necessary. The package provides type-3 ANOVA output with degrees of freedom corrected F-tests for fixed-effects, which makes the package unique in open source implementations of mixed models. The approach together with the user-friendliness of the package allow to analyze a broad range of mixed effects models in a fast and efficient way. The benefits of the approach and the package are illustrated on four data sets coming from consumer/sensory studies. 2014 Elsevier Ltd. All rights reserved.
8 citations
TL;DR: A multivariate generalization of the multiplicative assessor model will be proposed, which allows to analyse the differences in the use of the scale with reference to the existing structure of relationships between sensory descriptors.
Abstract: Data from descriptive sensory analysis are essentially three-way data with assessors, samples and attributes as the three ways in the data set. Because of this, there are several ways that the data can be analysed. The paper focuses on the analysis of sensory characteristics of products while taking into account the individual differences among assessors. In particular, we will be interested in considering the multiplicative assessor model, which explicitly models the different usage of scale. A multivariate generalization of the model will be proposed, which allows to analyse the differences in the use of the scale with reference to the existing structure of relationships between sensory descriptors. The multivariate assessor model will be tested on a data set from milk. Relations between the proposed model and other multiplicative models like parallel factor analysis and analysis of variance will be clarified. Copyright © 2014 John Wiley & Sons, Ltd.
6 citations