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SAS Essentials: Mastering SAS for Data Analytics, 2nd Edition by Wayne A. Woodward, Alan C. Elliott

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14ANALYSIS OF VARIANCE, PART II

SAS provides procedures that can analyze data from a wide range of experimental designs. This chapter illustrates three designs not previously discussed in Chapter 13 and provides you with a brief introduction to PROC MIXED.

14.1 ANALYSIS OF COVARIANCE

An analysis of covariance (ANCOVA) is a combination of analysis of variance and regression. The covariate is a quantitative variable that is related to the dependent variable. However, the covariate is not controlled by the investigator but is some value intrinsic to the subject (or entity). In ANCOVA, the group means are adjusted by the covariate, and these adjusted means are compared with each other. Including this covariate variable in the model may explain some of the variability, resulting in a more powerful statistical test.

Consider an experiment designed to compare three medications for lowering systolic blood pressure (SBP). A potentially useful covariate would be age because it is known that there is a relationship between SBP and age. If SBP is the dependent variable in a model, it might be helpful to adjust SBP by the covariate age. Thus, in an ANCOVA, the means adjusted for ...

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