Abstract
CHAPTER 1: Introduction to Design CHAPTER 2: Principles of Estimation and Inference: Means and Variance CHAPTER 3: Design and Analysis of Single-Factor Experiments: Completely Randomized Design CHAPTER 4: Single-Factor Experiments Having Repeated Measures on the Same Element CHAPTER 5: Design and Analysis of Factorial Experiments: Completely-Randomized Design CHAPTER 6: Factorial Experiments: Computational Procedures and Numerical Example CHAPTER 7: Multifactor Experiments Having Repeated Measures on the Same Element CHAPTER 8: Factorial Experiments in which Some of the Interactions are Confounded CHAPTER 9: Latin Squares and Related Designs CHAPTER 10: Analysis of Covariance
Keywords
Computer science
Affiliated Institutions
Related Publications
Evaluating the Impact of Partial Factorial Invariance on Selection in Two Populations.
Studies of factorial invariance examine whether a common factor model holds across multiple populations with identical parameter values. Partial factorial invariance exists when...
Dynamic wait-listed designs for randomized trials: new designs for prevention of youth suicide
Background The traditional wait-listed design, where half are randomly assigned to receive the intervention early and half are randomly assigned to receive it later, is often ac...
Mean and Covariance Structures (MACS) Analyses of Cross-Cultural Data: Practical and Theoretical Issues
Practical and theoretical issues are discussed for testing (a) the comparability, or measurement equivalence, of psychological constructs and (b) detecting possible sociocultura...
Bayes Estimates for the Linear Model
Summary The usual linear statistical model is reanalyzed using Bayesian methods and the concept of exchangeability. The general method is illustrated by applications to two-fact...
An <i>R</i><sup>2</sup> statistic for fixed effects in the linear mixed model
Abstract Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R 2 statistic in the linear univariate model...
Publication Info
- Year
- 1962
- Type
- book
- Citations
- 26927
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
26927
OpenAlex
Cite This
B. J. WINER
(1962).
Statistical principles in experimental design..
McGraw-Hill Book Company
.
https://doi.org/10.1037/11774-000
Identifiers
- DOI
- 10.1037/11774-000