A design matrix is a matrix that is used in the certain statistical models, e.g., the general linear model. It can contain indicator variables (ones and zeros) that indicates group membership in an ANOVA and it represents the independent variables. The advantage with a design matrix is that it is able to represent a number of different experimental designs and statistical models, e.g., ANOVA, ANCOVA, and linear regression
Example
One-way ANOVA
Example with a one-way ANOVA with 3 groups and 7 observations. The first column in the design matrix models the grand mean of the ys, while the 3 remaining columns indicate the group membership of each observation. Here the first group consists of the 3 first observations and the next two groups each consist of two observations.
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The DesignMatrix allows additional constraints to be placed on the real parameter estimates through the definition of the beta parameters, or to specify individual covariates to be included in the model.
Columns in the designmatrix can also be labeled so that you can interpret the structure of the model both when the model is retrieved or viewing the beta parameter estimates.
Useful options for large, complicated design matrices are to Save the current designmatrix to a dBase (DBF) file, edit the designmatrix with a spreadsheet program, copy the designmatrix to the clipboard from the spreadsheet, and then Paste the clipboard back into the designmatrix.
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