- One-way ANCOVA: analysis of covariance
- can be thought of as an extension of the one-way ANOVA to incorporate a covariate.
- used to determine whether there are any significant differences between two or more independent (unrelated) groups on a dependent variable.
- whereas the ANOVA looks for differences in the group means, the ANCOVA looks for differences in adjusted means (i.e., adjusted for the covariate).
Nine assumptions before one-way ANCOVA
- dependent variable and covariate variable(s) should be measured on a continuous scale (i.e., they are measured at the interval or ratio level)
- independent variable should consist of two or more categorical, independent groups.
- independence of observations, which means that there is no relationship between the observations in each group or between the groups themselves.
- no significant outliers.
- residuals should be approximately normally distributed for each category of the independent variable. You can test for normality using two Shapiro-Wilk tests of normality: one to test the within-group residuals and one to test the overall model fit.
- homogeneity of variances. You can test this assumption in SPSS Statistics using Levene’s test for homogeneity of variances.
- covariate should be linearly related to the dependent variable at each level of the independent variable. You can test this assumption in SPSS Statistics by plotting a grouped scatterplot of the covariate, post-test scores of the dependent variable and independent variable.
- There needs to be homoscedasticity.
- There needs to be homogeneity of regression slopes, which means that there is no interaction between the covariate and the independent variable.
Test Procedure in SPSS Statistics
- Click Analyze > General Linear Model > Univariate… on the main menu
- Transfer the dependent variable into the Dependent Variable box, the independent variable, into the Fixed Factor(s): box, and the covariate into the Covariate(s): box, by selecting each variable (by clicking on it) and clicking the relevant button.
Reference:
https://statistics.laerd.com/spss-tutorials/ancova-using-spss-statistics.php#procedure
