Fills need in existing literature for textbook on R and Psychometrics
Broadens perspective from classical methods (for instance, latent variable models) to emphasize contemporary methodology (multidimensional scaling, functional data analysis, fMRI analysis)
Accompanying datasets and reproducible code allow readers to move beyond the conceptual

Fills need in existing literature for textbook on R and Psychometrics Broadens perspective from classical methods (for instance, latent variable models) to emphasize contemporary methodology (multidimensional scaling, functional data analysis, fMRI analysis) Accompanying datasets and reproducible code allow readers to move beyond the conceptual Includes supplementary material: sn.pub/extras

Autorentext
Patrick Mair is Senior Lecturer in Statistics in the Department of Psychology at Harvard University. His research focuses on computational and applied statistics with special emphasis on psychometric methods, such as latent variable models and multivariate exploratory techniques. Mair holds a doctorate in Statistics and a master's degree in Psychology from the University of Vienna. He was also a Research Fellow at the Department of Statistics at the University of California, Los Angeles.

Zusammenfassung
Fills need in existing literature for textbook on R and Psychometrics
Broadens perspective from classical methods (for instance, latent variable models) to emphasize contemporary methodology (multidimensional scaling, functional data analysis, fMRI analysis)
Accompanying datasets and reproducible code allow readers to move beyond the conceptual

Inhalt
Classical Test Theory.-Factor Analysis.- Path Analysis and Structural Equation Models.- Item Response Theory.- Preference Modeling.- Principal Component Analysis and Extensions.- Correspondence Analysis.- Gifi Methods.- Multidimensional Scaling.- Biplots.- Networks.- Parametric Cluster Analysis and Mixture Regression.- Modeling Trajectories and Time Series.- Analysis of fMRI Data.