This paper presents the results of a double-blind ANOVA study on the relationship between Repeated Measures Interactions and Regression Correlation and Covariance Effect Size in the context of Messy Data.
Preface Data, Samples and Statistics Probability Distributions Confidence Intervals Significance Tests Regression Correlation and Covariance Effect Size Statistical Power Exploring Messy Data Dealing with Messy Data Alternatives to Classical Statistical Inference Multiple Regression and the General Linear Model ANOVA and ANCOVA with Independent Measures Interactions Contrasts Repeated Measures ANOVA Modelling Discrete Outcomes Multilevel Models References