42 results on '"Kuesten, Carla"'
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2. Functional Foods and Protein Supplementation
3. Using functional data analysis (FDA) for time-intensity (T-I) evaluation of perceptual efficacy, exemplified by a supplement tablet longitudinal study
4. Functional Foods and Dietary Supplements
5. Functional Foods and Protein Supplementation
6. Chapter 4 | Methods
7. Thurstonian models for three variants (specified, unspecified, and unspecified with forgiveness) of the Two‐Out‐of‐Five method
8. Time‐intensity data analysis in terms of R‐index measures transformed from menopause rating scale data collected in a longitudinal menopause tablet perceptual efficacy study
9. Functional Foods and Protein Supplementation
10. Functional Foods and Dietary Supplements
11. Healthcare supplements in context
12. Contributors
13. Type I error, testing power, and predicting precision based on the GLM and LM models for CATA data--Further discussion with M. Meyners and A. Hasted
14. Sparse hierarchical clustering based on Menopause Rating Scale severity of symptoms collected from perimenopausal and postmenopausal US women in a menopause tablet perceptual efficacy study
15. Comprehensive model for characterizing skin translucency by expert grading, panel evaluation and image analysis in a Chinese population
16. Japanese consumer segmentation based on general self-efficacy psychographics data collected in a phytonutrient supplement study: Influence on health behaviors, well-being, product involvement and liking
17. Time-Intensity Using Discrete Time Points
18. Commentary on Meyners and Hasted (2021): On the applicability of ANOVA models for CATA data, Food Quality and Preference, 92
19. The paired A‐Not A with AB and BA pairs
20. The Use of Demographics and Psychographics to Study Product Effects with Nutrient Supplements: Exploratory Multi-Country Data
21. TURF analysis for CATA data using R package ‘turfR’
22. Application of a panel performance reliability versus product effect size (PR-ES) framework: A protein powder case study
23. Human Skin Gloss Perception Based on Texture Statistics
24. The paired A‐Not A with AB and BA pairs.
25. 17 - Healthcare supplements in context
26. A more powerful non‐attribute‐specified sensory discrimination method: The paired unspecified tetrad with different order ( AB and BA ) pairs
27. Review and development of Thurstonian models for the triangle and duo‐trio methods and paired versions of the methods
28. Paired versions of the triangle and duo-trio methods with AB and BA pairs
29. The four-interval, two-alternative forced-choice (4I2AFC): A powerful sensory discrimination method to detect small, directional changes particularly suitable for visual or manual evaluations
30. Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews
31. Assessing gloss perception of human facial skin across subject
32. Paired versions of various sensory discrimination forced-choice methods and the same-different area theorem
33. Analyzing consumers’ Profile of Mood States (POMS) data using the proportional odds model (POM) for clustered or repeated observations and R package ‘repolr’
34. Determining the Influence of Image-based Cues on Human Skin Gloss Perception
35. Case studies of industrial applications of the “M+N” classification method with larger M and N for visual and manual inspections
36. A Simplified Form of the Psychometric Function for the m -Alternative Forced Choice (m AFC) Method
37. Propensity score analysis (PSA) for sensory causal inference – Global consumer psychographics and applications for phytonutrient supplements
38. Sensory Measurements for the Method of “M+N” with Larger M and N
39. Revisiting Fisher’s ‘Lady Tasting Tea’ from a perspective of sensory discrimination testing
40. Risk Assessment of Negative Sensory Effects in Product Development Using the Benchmark Dose (BMD) Methodology for Continuous Data
41. Estimating and Testing Parameters of the Thurstonian Model for Torgerson's Method of Triads
42. A Simplified Form of the Psychometric Function for the m-Alternative Forced Choice ( mAFC) Method.
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