The General Linear Model: A Primer

·
· Cambridge University Press
Kitabu pepe
191
Kurasa
Ukadiriaji na maoni hayajahakikishwa  Pata Maelezo Zaidi

Kuhusu kitabu pepe hiki

General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis. This volume fills this void by introducing the General Linear Model (GLM), whose basic concept is that an observed variable can be explained from weighted independent variables plus an additive error term that reflects imperfections of the model and measurement error. It also covers multivariate regression, analysis of variance, analysis under consideration of covariates, variable selection methods, symmetric regression, and the recently developed methods of recursive partitioning and direction dependence analysis. Each method is formally derived and embedded in the GLM, and characteristics of these methods are highlighted. Real-world data examples illustrate the application of each of these methods, and it is shown how results can be interpreted.

Kuhusu mwandishi

Alexander von Eye is Professor Emeritus of Psychology at Michigan State University, USA. He received his Ph.D. in Psychology from the University of Trier, Germany, in 1976. He is known for his work on statistical modeling, categorical data analysis, and person-oriented research. Recognitions include an honorary professorship of the Technical University of Berlin, fellow status of the APA and the APS, and he was named Accredited Professional StatisticianTM (PSTATTM) of the American Statistical Association. He authored, among others, texts on Configural Frequency Analysis, and he edited, among others, books on Statistics and Causality (2016) and on direction dependence (2021). His over 400 articles appeared in the premier journals of the field, including, for instance, Psychological Methods, Multivariate Behavioral Research, Child Development, Development and Psychopathology, the Journal of Person-Oriented Research, the American Statistician, and the Journal of Applied Statistics.

Wolfgang Wiedermann is Associate Professor at the University of Missouri, USA. He received his Ph.D. in Quantitative Psychology from the University of Klagenfurt, Austria. His primary research interests include the development of methods for causal inference, methods to evaluate the causal direction of dependence, and methods for person-oriented research. He has edited books on new developments in statistical methods for dependent data analysis in the social and behavioral sciences (2015), advances in statistical methods for causal inference (2016) and causal direction of dependence (2021). His work appears in leading journals of the field, including Psychological Methods, Multivariate Behavioral Research, Behavior Research Methods, Developmental Psychology, and Development and Psychopathology. Recognitions include the Young Researcher Award 2021 by the Scandinavian Society for Person-Oriented Research.

Kadiria kitabu pepe hiki

Tupe maoni yako.

Kusoma maelezo

Simu mahiri na kompyuta vibao
Sakinisha programu ya Vitabu vya Google Play kwa ajili ya Android na iPad au iPhone. Itasawazishwa kiotomatiki kwenye akaunti yako na kukuruhusu usome vitabu mtandaoni au nje ya mtandao popote ulipo.
Kompyuta za kupakata na kompyuta
Unaweza kusikiliza vitabu vilivyonunuliwa kwenye Google Play wakati unatumia kivinjari cha kompyuta yako.
Visomaji pepe na vifaa vingine
Ili usome kwenye vifaa vya wino pepe kama vile visomaji vya vitabu pepe vya Kobo, utahitaji kupakua faili kisha ulihamishie kwenye kifaa chako. Fuatilia maagizo ya kina ya Kituo cha Usaidizi ili uhamishe faili kwenye visomaji vya vitabu pepe vinavyotumika.