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Imputation
Acceptability For Sale
Agency Testing
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Multiple Factor Analysis (MFA)
Statistical techniques for estimating and filling in missing sensory data values, enabling complete analyses when incomplete data would otherwise compromise multivariate methods.
November 15, 2016
Handling missing data in consumer hedonic tests arising from direct scaling
July 29, 2016
Appropriate Methods of Imputation for Consumer Hedonic Data
September 22, 2015
Product selection for liking studies: the sensory-informed design
September 17, 2014
Combining highly efficient methods can reduce costs without compromise
August 11, 2013
Sensory informed design: An effective clustering of incomplete block consumer data
July 13, 2012
Sensory Informed Incomplete Block Designs
July 12, 2012
A New Method for Analyzing Time Intensity Curves
July 25, 2010
The effect of an incomplete block design on consumer segmentation
July 26, 2009
Segmentation of BIB consumer liking of high-fatigue products: Sensory confirmation of statistical methods
July 21, 2008
Consumer segmentation of BIB liking data of 12 cabernet sauvignon wines: A case study