Focusing on situations in which analysis of variance (ANOVA) involving the repeated measurement of separate groups of individuals is needed, Girden reveals the advantages, disadvantages, and counterbalancing issues of repeated measures situations. Using additive and nonadditive models to guide the analysis in each chapter, the book covers such topics as the rationale for partitioning the sum of squares, detailed analyses to facilitate the interpretation of computer printouts, the rationale for the F ratios in terms of expected means squares, validity assumptions for sphericity or circularity and approximate tests to perform when sphericity is not met.
ANOVA
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First Sentence:
Analysis of variance, in its simplest form, is a general procedure for isolating the sources of variability in a set of measurement. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
separate error terms, nonadditive model, repeated measures factor, circularity assumption, appropriate error term, compound symmetry, partial interactions, prime type, triple interaction, maternal acceptance, simple main effects, grand mean, tabled value, more powerful test, mixed design, univariate test New!
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Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
Analysis of variance, in its simplest form, is a general procedure for isolating the sources of variability in a set of measurement. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
separate error terms, nonadditive model, repeated measures factor, circularity assumption, appropriate error term, compound symmetry, partial interactions, prime type, triple interaction, maternal acceptance, simple main effects, grand mean, tabled value, more powerful test, mixed design, univariate test New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
Citations (learn more)
This book cites 68
books:
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1
book
cites this book:
- Analysis of Variance (Quantitative Applications in the Social Sciences) by Gudmund R. Iversen in Back Matter (1), and Back Matter (2)
- Multivariate Analysis of Variance (Quantitative Applications in the Social Sciences) by James H. Bray in Back Matter (1), and Back Matter (2)
- Analyzing Panel Data (Quantitative Applications in the Social Sciences) by Gregory B. Markus in Back Matter
- Causal Modeling (Quantitative Applications in the Social Sciences) by Herbert B. Asher in Back Matter
- Tests of Significance (Quantitative Applications in the Social Sciences) by Ramon E. Henkel in Back Matter
See all 68 books this book cites
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