Buch, Englisch, 521 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 975 g
Using R and SAS
Buch, Englisch, 521 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 975 g
Reihe: Springer Series in Statistics
ISBN: 978-3-030-02912-8
Verlag: Springer International Publishing
This book explains how to analyze independent data from factorial designs without having to make restrictive assumptions, such as normality of the data, or equal variances. The general approach also allows for ordinal and even dichotomous data. The underlying effect size is the nonparametric relative effect, which has a simple and intuitive probability interpretation. The data analysis is presented as comprehensively as possible, including appropriate descriptive statistics which follow a nonparametric paradigm, as well as corresponding inferential methods using hypothesis tests and confidence intervals based on pseudo-ranks.
Offering clear explanations, an overview of the modern rank- and pseudo-rank-based inference methodology and numerous illustrations with real data examples, as well as the necessary R/SAS code to run the statistical analyses, this book is a valuable resource for statisticians and practitioners alike.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Pharmazie
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie
Weitere Infos & Material
1 Types of Data and Designs.- 2 Distributions and Effects.- 3 Two Samples.- 4 Several Samples.- 5 Two-Factor Crossed Designs.- 6 Designs with Three and More Factors.- 7 Derivation of Main Results.- 8 Mathematical Techniques.- References.- A Software and Program Code.- B Data Sets and Descriptions.- Index.