| 书目名称 | Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs | | 副标题 | Using R and SAS | | 编辑 | Edgar Brunner,Arne C. Bathke,Frank Konietschke | | 视频video | | | 概述 | Offers a detailed overview of the modern rank- and pseudo-rank-based inference methodology.Richly illustrated with examples.Provides codes (R, SAS) for the statististical analysis.Includes supplementa | | 丛书名称 | Springer Series in Statistics | | 图书封面 |  | | 描述 | .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. .. . | | 出版日期 | Book 2018 | | 关键词 | Factorial designs; Nonparametric Statistics; Multiple contrast tests; Sample Size Planning; Nonparametri | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-02914-2 | | isbn_ebook | 978-3-030-02914-2Series ISSN 0172-7397 Series E-ISSN 2197-568X | | issn_series | 0172-7397 | | copyright | Springer Nature Switzerland AG 2018 |
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发表于 2025-3-21 17:53:12
