Traditional and GLM Approaches to Independent Measures Single Factor ANOVA Designs
Andrew Rutherford
Abstract
Andrew Rutherford
Abstract
The type of experimental design determines the particular form of analysis of variance (ANOVA) that should be applied. A wide variety of experimental designs and pertinent ANOVA procedures are available. The simplest of these are independent measures designs. A balanced data design has the same number of subjects in each experimental condition. While there should be some logical relation between the levels of any factor, they may not be linked in such a continuous fashion as is suggested by the term independent variable. So, from now on, the label, Factor, will be used in preference. A confidence interval specifies the range within which it is expected that a particular estimate will occur. General linear model (GLM) equations for ANOVA have become common sights in statistical texts, even when a traditional approach to ANOVA is applied. Controlled Vocabulary Terms analysis of variance; Balanced data design; confidence interval; independent variables
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The type of experimental design determines the particular form of analysis of variance (ANOVA) that should be applied. A wide variety of experimental designs and pertinent ANOVA procedures are available. The simplest of these are independent measures designs. A balanced data design has the same number of subjects in each experimental condition. While there should be some logical relation between the levels of any factor, they may not be linked in such a continuous fashion as is suggested by the term independent variable. So, from now on, the label, Factor, will be used in preference. A confidence interval specifies the range within which it is expected that a particular estimate will occur. General linear model (GLM) equations for ANOVA have become common sights in statistical texts, even when a traditional approach to ANOVA is applied. Controlled Vocabulary Terms analysis of variance; Balanced data design; confidence interval; independent variables
Key concepts: Statistics, Analysis of variance, Mathematics, Variance (accounting), Confidence interval, Mixed-design analysis of variance, Main effect, Range (aeronautics)