Sebastian Kaiser

TL;DR: In this article, a comprehensive simulation study is conducted aimed at identifying the influence of different factors on the predictive validity of single versus multi-item measures, such as the average inter-item correlations in the predictor and criterion constructs, the number of items measuring these constructs, as well as the correlation patterns of multiple and single items between the predictor between the criterion constructs.

TL;DR: In this article, a comprehensive simulation study is conducted aimed at identifying the influence of different factors on the predictive validity of single versus multi-item measures, such as the average inter-item correlations in the predictor and criterion constructs, the number of items measuring these constructs, as well as the correlation patterns of multiple and single items between the predictor between the criterion constructs.

TL;DR: In this article, the authors introduce biclustering, a novel approach to address the problem of high dimensionality in tourism segmentation studies, which aims to identify market segments among tourists who are similar to each other, thus allowing a targeted marketing mix to be developed.

TL;DR: The S4VD algorithm is proposed to incorporate stability selection to improve this method, which is the first biclustering approach that takes the cluster stability regarding perturbations of the data into account.

TL;DR: The R package biclust is introduced, which contains a collection of bicluster algorithms, preprocessing methods for two way data, and validation and visualization techniques for bicuster results.