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Performing an analysis of covariance (ANCOVA)

Test if there is a difference between population means when a response variable is classified by one or more categorical variables (factors) while adjusting for the effect of one or more quantitative variables (covariates).

  1. Select a cell in the dataset.
  2. On the Analyse-it ribbon tab, in the Statistical Analyses group, click Fit Model, and then click ANCOVA.
    The analysis task pane opens.
  3. In the Y drop-down list, select the response variable.
  4. In the Available variables list, select the variable(s):
    • To select a single variable, click the variable.
    • To select multiple variables, click the first variable then hold down the CTRL key and click each additional variable.
    • To select a range of variables, click the first variable then hold down the SHIFT key and click the last variable in the range.
  5. To add the variables to the model as categorical factors, click Add Factor.
  6. To add the variables to the model as quantitative covariates, click Add Covariate.
  7. To add the interaction between two or more factors/covariates, in the Terms list box, click the first term then hold down the CTRL key and click each additional term to include in the interaction, and then click Cross.
  8. To remove a term, in the Terms list box, click the term and then click Remove.
    Note: It is sometimes quicker to use the Factorial command to build a model and then remove any unnecessary terms.
  9. To remove a factor/covariate and all terms using the factor/covariate, in the Factors or Covariates list box, click the factor/covariate and then click Remove.

    When you select a factor or covariate, all terms that include the factor or covariate are selected. If you hold down the CTRL key and click additional factors or covariates, then all terms which include all the selected factors or covariates are selected.

  10. Repeat steps 4 through 9 to build the model.
  11. Click Calculate.
Related concepts
Effect of model hypothesis test
Effect of terms hypothesis test
Effect means
Related tasks
Plotting main effects and interactions
Comparing effect means
Related reference
Dataset layout
Advanced models
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Version 6.15
Published 18-Apr-2023
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