| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4317131 | Food Quality and Preference | 2014 | 10 Pages |
Abstract
•Comparison of alternative ways to analyzing designed experiments.•Splitting data sets can enhance information of less dominating effects.•Combinations of ANOVA and PCA provide additional insight.
This paper presents a comparison of different methods for analyzing designed experiments. The methods used are based on PCA, PLS and ANOVA, used either separately or in combination. Special emphasis will be on how to obtain information about medium and less important factors in the presence of very dominating ones. It will be shown that this could be done by splitting the dataset in two. Our propositions will be illustrated on a data set obtained for studying the effect of salt reduction in liver paste.
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Authors
Tormod Næs, Oliver Tomic, Kirsti Greiff, Kari Thyholt,