Methods for imputation of missing values and their influence on the results of segmentation research

• Authors: Gąsior Marcin , Skowron Łukasz

Title variants

PL

Metody uzupełniania braków danych i ich wpływ na wyniki badań segmentacyjnych.

• Languages of publication: EN

Abstracts

EN

The lack of answers is a common problem in all types of research, especially in the field of social sciences. Hence a number of solutions were developed, including the analysis of complete cases or imputations that supplement the missing value with a value calculated according to different algorithms. This paper evaluates the influence of the adopted method for the supplementation of missing answers regarding the result of segmentation conducted with the use of cluster analysis. In order to achieve this we used a set of data from an actual consumer research in which the cases with missing values were deleted or supplemented with the use of various methods. Cluster analyses were then performed on those sets of data, both with the assumption of ordinal and ratio level of measurement, and then the grouping quality, as expressed by different indicators, was evaluated. This research proved the advantage of imputation over the analysis of complete cases, it also proved the validity of using more complex approaches than the simple supplementation with an average or median value.

Keywords

EN

missing values; cluster analysis; k-means algorithm; k-medoids algorithm

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Econometrics. Ekonometria. Advances in Applied Data Analytics
• Year: 2016
• Issue: 4 (54)
• Pages: 61-71

Contributors

author

Gąsior Marcin

author

Skowron Łukasz

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