Appropriate Methods of Imputation for Consumer Hedonic Data
The challenge is to perform appropriate data imputation for 570 consumers, each of whom evaluates 6 brown breads in a 16-present-6 sensory-informed balanced incomplete block design. These data were previously analyzed and discussed [1]. Data are available (i) in the R package sensory (see bbread), and (ii) on the Sensometrics Data Set Repository (see Brown Bread data). [1] Franczak, B. C., Browne, R. P., McNicholas, P. D. & Findlay, C. J. (2015). Product selection for liking studies: The sensory informed design. Food Quality and Preference, 44, 36–43.
Findlay, C. J., Castura, J. C., & McNicholas, P. D. (Eds). (2016). Data Analysis Workshop: Appropriate Methods of Imputation for Consumer Hedonic Data. In: 13th Sensometrics Meeting. 27-29 July. Brighton, UK. (Chair: Findlay, C. J.; Presenters: P. D. McNicholas, E. Vigneau, & P. Schlich).