Multivariate and Probabilistic Analyses of Sensory Science Problems -- Table of Contents -- Introduction -- Chapter 1. A Description of Sample Data Sets Used in Further Chapters -- 1.1. A Description of Example Data Sets -- References -- Chapter 2. Panelist and Panel Performance: A Multivariate Experience -- 2.1. The Multivariate Nature of Sensory Evaluation -- 2.2. Univariate Approaches to Panelist Assessment -- 2.3. Multivariate Techniques for Panelist Performance -- 2.4. Panel Evaluation through Multivariate Techniques -- 2.5. Conclusions -- References -- Chapter 3. A Nontechnical Description of Preference Mapping -- 3.1. Introduction -- 3.2. Internal Preference Mapping -- 3.3. External Preference Mapping -- 3.4. Conclusions -- References -- Chapter 4. Deterministic Extensions to Preference Mapping Techniques -- 4.1. Introduction -- 4.2. Application and Models Available -- 4.3. Conclusions -- References -- Chapter 5. Multidimensional Scaling and Unfolding and the Application of Probabilistic Unfolding to Model Preference Data -- 5.1. Introduction -- 5.2. Multidimensional Scaling (MDS) and Unfolding -- 5.3. Probabilistic Approach to Unfolding and Identifying the Drivers of Liking -- 5.4. Examples -- References -- Chapter 6. Consumer Segmentation Techniques -- 6.1. Introduction -- 6.2. Methods Available -- 6.3. Segmentation Methods Using Hierarchical Cluster Analysis -- References -- Chapter 7. Ordinal Logistic Regression Models in Consumer Research -- 7.1. Introduction -- 7.2. Limitations of Ordinary Least Squares Regression -- 7.3. Odds, Odds Ratio, and Logit -- 7.4. Binary Logistic Regression -- 7.5. Ordinal Logistic Regression Models -- 7.6. Porportional Odds Model (POM) -- 7.7. Conclusions -- References -- Chapter 8. Risk Assessment in Sensory and Consumer Science -- 8.1. Introduction -- 8.2. Concepts of Quantitative Risk Assessment.

8.3. A Case Study: Cheese Sticks Appetizers -- 8.4. Conclusions -- References -- Chapter 9. Application of MARS to Preference Mapping -- 9.1. Introduction -- 9.2. MARS Basics -- 9.3. Setting Control Parameters and Refining Models -- 9.4. Example of Application of MARS -- 9.5. A Comparison with PLS Regression -- References -- Chapter 10. Analysis of Just About Right Data -- 10.1. Introduction -- 10.2. Basics of Penalty Analysis -- 10.3. Boot strapping Penalty Analysis -- 10.4. Use of MARS to Model JAR Data -- 10.5. A Proportional Odds/Hazards Approach to Diagnostic Data Analysis -- 10.6. Use of Dummy Variables to Model JAR Data -- References -- Index.