Why covariance analysis should replace increment analysis of variance in caries studies
Malcolm J. Slakter, Bill Wu
Abstract
Malcolm J. Slakter, Bill Wu
Abstract
Consider a caries study where experimental units are a) randomly assigned to groups, b) premeasured on DMFS, c) administered a specified treatment depending on group membership, and d) postmeasured on DMFS. Traditional analysis of these data consists of analysis of variance of the increment scores (increment ANOVA). In the place of increment ANOVA, others have suggested analysis of covariance with the postmeasure as criterion and the premeasure of covariate (ANOCOV). The present paper examines and documents the following: 1) Increment ANOVA and ANOCOV test the same null hypothesis. 2) Increment ANOVA and ANOCOV have exactly the same assumptions. 3) Increment ANOVA is usually less precise than ANOCOV. 4) The same concern for violations of assumptions must be expressed with increment ANOVA as with ANOCOV (see No. 2 above). 5) ANOCOV should replace increment ANOVA in caries studies (see points 1-4).
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Consider a caries study where experimental units are a) randomly assigned to groups, b) premeasured on DMFS, c) administered a specified treatment depending on group membership, and d) postmeasured on DMFS. Traditional analysis of these data consists of analysis of variance of the increment scores (increment ANOVA). In the place of increment ANOVA, others have suggested analysis of covariance with the postmeasure as criterion and the premeasure of covariate (ANOCOV). The present paper examines and documents the following: 1) Increment ANOVA and ANOCOV test the same null hypothesis. 2) Increment ANOVA and ANOCOV have exactly the same assumptions. 3) Increment ANOVA is usually less precise than ANOCOV. 4) The same concern for violations of assumptions must be expressed with increment ANOVA as with ANOCOV (see No. 2 above). 5) ANOCOV should replace increment ANOVA in caries studies (see points 1-4).
Key concepts: Analysis of variance, Analysis of covariance, Mixed-design analysis of variance, Repeated measures design, Statistics, One-way analysis of variance, Covariate, Medicine