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A COMPARISON OF THREE COMMONLY USED METHODS FOR TREATING NO PREFERENCE VOTES
Author(s) -
ENNIS JOHN M.,
ENNIS DANIEL M.
Publication year - 2012
Publication title -
journal of sensory studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 53
eISSN - 1745-459X
pISSN - 0887-8250
DOI - 10.1111/j.1745-459x.2012.00374.x
Subject(s) - preference , computer science , type i and type ii errors , interpretation (philosophy) , statistics , mathematics , econometrics , data mining , programming language
The treatment of no preference votes continues to be an issue in sensory science, especially as the proper treatment of these votes has recently gained importance in advertising claims support. There are currently three main methods in common use: dropping the no preference votes, splitting the votes equally and splitting the votes proportionally according to the results among those who expressed a preference. The analyses then proceed as if the data were binomially distributed. In this paper, we compare these methods with respect to power and type I error. We show that proportional splitting returns more false alarms than expected and hence should not be used. We then discuss the meaningful interpretation of statistical significance in the presence of large numbers of no preference votes before providing general recommendations and indicating a promising direction of future research in this area. PRACTICAL APPLICATIONS When researchers choose a specific method of data analysis, they implicitly choose the effect of that analysis on their conclusions. Thus, it is important to compare rival methods of analysis where they exist. In the case of handling no preference votes, three analytic methods are in common use. These methods – dropping, equal splitting and proportional splitting – are compared in this paper with respect to power and type I error. This comparison, together with the ensuing discussion and recommendations, helps researchers make more informed decisions in their choice of analytic method for data that includes no preference votes.