Cited by 8,539Optimal Experimental Design MethodsStatistical Methods and Bayesian InferenceStatistical Methods and Applications

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Experimental Design: Procedures for the Behavioral Sciences

Kirk, Roger·2013·Sage eBooks

DOI 10.4135/9781483384733

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Abstract

Chapter 1. Research Strategies and the Control of Nuisance Variables Chapter 2. Experimental Designs: an Overview Chapter 3. Fundamental Assumptions in Analysis of Variance Chapter 4. Completely Randomized Design Chapter 5. Multiple Comparison Tests Chapter 6. Trend Analysis Chapter 7. General Linear Model Approach to ANOVA Chapter 8. Randomized Block Designs Chapter 9. Completely Randomized Factorial Design with Two Treatments Chapter 10. Completely Randomized Factorial Design with Three or More Treatments and Randomized Block Factorial Design Chapter 11. Hierarchical Designs Chapter 12. Split-Plot Factorial Design: Design with Group-Treatment Confounding Chapter 13. Analysis of Covariance Chapter 14. Latin Square and Related Designs Chapter 15. Confounded Factorial Designs: Designs with Group-Interaction Confounding Chapter 16. Fractional Factorial Designs: Designs with Treatment-Interaction Confounding

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Authors: Kirk, R.
Corresponding author: Kirk, Roger
Venue: Sage eBooks
Publisher: SAGE Publications, Inc.
Published: 2013
DOI: 10.4135/9781483384733
OpenAlex: W2134654456
Cited by: 8,539
References: 0
Citations by year: 2026: 23 · 2025: 40 · 2024: 50 · 2023: 48 · 2022: 64 · 2021: 64 · 2020: 78 · 2019: 65 · 2018: 94 · 2017: 98 · 2016: 105 · 2015: 83 · 2014: 107 · 2013: 127
FWCI: 44.24
Type: book
Language: en
Open access: closed
Locations: Sage eBooks (publishedVersion)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords: experimental design, behavioral science, nuisance parameters, analysis of variance, completely randomized design, multiple comparison tests, trend analysis, general linear model, randomized block design, factorial design, hierarchical design, split-plot design, covariance analysis, Latin square design, fractional factorial design

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Experimental Design: Procedures for the Behavioral Sciences

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