ANOVA and mixed models : a short introduction using R

著者
    • Meier, Lukas
書誌事項

ANOVA and mixed models : a short introduction using R

Lukas Meier

(The R series)

CRC Press, 2023

  • : hbk

この図書・雑誌をさがす
注記

Includes bibliographical references (p. 179-184) and index

内容説明・目次

内容説明

Features Accessible to readers with a basic background in probability and statistics Covers fundamental concepts of experimental design and cause-effect relationships Introduces classical ANOVA models, including contrasts and multiple testing Provides an example-based introduction to mixed models Features basic concepts of split-plot and incomplete block designs R code available for all steps Supplementary website with additional resources and updates

目次

1. Learning from Data. 1.1. Cause-Effect Relationships. 1.2. Experimental Studies. 2. Completely Randomized Designs. 2.1. One-Way Analysis of Variance. 2.2. Checking Model Assumptions. 2.3. Nonparametric Approaches. 2.4. Power or "What Sample Size Do I Need?". 2.5. Adjusting for Covariates. 2.6. Appendix. 3. Contrasts and Multiple Testing. 3.1. Contrasts. 3.2. Multiple Testing. 4. Factorial Treatment Structure. 4.1. Introduction. 4.2. Two-Way ANOVA Model. 5. Complete Block Designs. 5.1. Introduction. 5.2. Randomized Complete Block Designs (RCBD). 5.3. Nonparametric Alternatives. 5.4. Outlook: Multiple Block Factors. 6. Random and Mixed Effects Models. 6.1. Random Effects Models. 7. Split-Plot Designs. 7.1. Introduction. 7.2. Properties of Split-Plot Designs. 7.3. A More Complex Example in Detail: Oat Varieties. 8. Incomplete Block Designs. 8.1. Introduction. 8.2. Balanced Incomplete Block Designs (BIBD). 8.3. Analysis of Incomplete Block Designs. 8.4. Outlook. 8.5. Concluding Remarks. Bibliography. Index

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