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Contributions to Machine Learning and Psychometrics

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Contributions to Machine Learning and Psychometrics (English shop)

Computational, Graphical, and Statistical Methods for Assessing Stability

Michel Philipp (Author)

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This work comprises several research contributions on the development of new methods for assessing the stability of statistical data analyses as conducted in research and practice. Stability is an important prerequisite for drawing consistent conclusions from the results of statistical data analyses. This is only possible, however, if analyses based on slightly modified or on completely different data sets from the same data-generating process lead to comparable interpretations. Moreover, stability is a central property of many psychometric models for ensuring objective and fair comparisons between persons.

ISBN-13 (Hard Copy) 9783736994478
ISBN-13 (eBook) 9783736984479
Final Book Format A5
Language English
Page Number 148
Lamination of Cover matt
Edition 1.
Publication Place Göttingen
Publication Date 2017-06-20
General Categorization Dissertation
Departments Psychology
Keywords stability, recursive partitioning, decision trees, variable selection, cutpoint selection, resampling, R package stablelearner, cognitive diagnosis model, G-DINA, standard errors, information matrix, differential item functioning, DINA model, Wald test, Lagrange multiplier test, score test