Cluster analysis refers to a wide range of data analytic techniques for class discovery and is
popular in many application fields. To assess the quality of a clustering result, different …

Although parenting styles constitute a well-known concept in parenting research, two issues
have largely been overlooked in existing studies. In particular, the psychological control …

Purpose The purpose of this paper is twofold. First, the authors provide a survey of
operations management (OM) research applications of traditional hierarchical and …

Using a conceptual, non-mathematical approach, the updated Third Edition provides full
coverage of the wide range of multivariate topics that graduate students across the social …

The k-means method aims to divide a set of N objects into k clusters, where each cluster is
represented by the mean value of its objects. This algorithm is simple and converges to local …

In unsupervised learning, the problem of finding the appropriate number of clusters-usually
notated as k-is very challenging. Its importance lies in the fact that k is a vital hyperparameter …

The present study investigates how teachers' motivation relates to burnout and engagement,
teaching style and need satisfaction at work. A total of 584 secondary teachers completed …

The use of growth modeling analysis (GMA)–particularly multilevel analysis and latent
growth modeling—to test the significance of intervention effects has increased exponentially …

The names of construction activities are the only unstructured data attribute in construction
schedules, and they often guide construction execution. Activity names are devised to …

The problem of partitioning a collection of objects based on their measurements on a set of
dichotomous variables is a well-established problem in psychological research, with …