Comparing Groups – Randomization and Bootstrap Methods Using R
Autor A Zieffleren Limba Engleză Hardback – 30 iun 2011
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Specificații
ISBN-13: 9780470621691
ISBN-10: 0470621699
Pagini: 332
Dimensiuni: 168 x 238 x 24 mm
Greutate: 0.61 kg
Editura: Wiley
Locul publicării:Hoboken, United States
ISBN-10: 0470621699
Pagini: 332
Dimensiuni: 168 x 238 x 24 mm
Greutate: 0.61 kg
Editura: Wiley
Locul publicării:Hoboken, United States
Public țintă
Researchers who need a practical guide to modern data analytic and computational methods, undergraduate and first–year graduate students in statistical methods, especially in the educational and behavioral sciences, including developmental psychology, clinical psychology, educational & school psychology, special education, epidemiology, family social science, kinesiology, communication disorders, education policy and administration, etc.; academic librariesCuprins
Notă biografică
Andrew S. Zieffler, PhD, is Lecturer in the Department of Educational Psychology at the University of Minnesota. Dr. Zieffler has published numerous articles in his areas of research interest, which include the measurement and assessment in statistics education research and statistical computing. Jeffrey R. Harring, PhD, is Assistant Professor in the Department of Measurement, Statistics, and Evaluation at the University of Maryland. Dr. Harring currently focuses his research on statistical models for repeated measures data and nonlinear structural equation models. Jeffrey D. Long, PhD, is Professor of Psychiatry in the Carver College of Medicine at The University of Iowa and Head Statistician for Neurobiological Predictors of Huntington's Disease (PREDICT-HD), a longitudinal NIH-funded study of early detection of Huntington's disease. His interests include the analysis of longitudinal and time-to-event data and ordinal data.
Descriere
Emphasizing the direct link between scientific research questions and data analysis, Modern Statistical and Computing Methods for the Behavioral and Educational Sciences Using R introduces current statistical methods, including the use of Monte Carlo simulation, bootstrapping, and randomization tests.