Variance components assess the amount of variation in the response because of random factors. To analyze a model with random factors, you usually use Fit Mixed Effects Model. While Fit General Linear Model also estimates variance components for random factors, Fit Mixed Effects Model provides better estimates when the designs are unbalanced. Fit General Linear Model and Fit Mixed Effects Model calculate the same variance components for balanced data.
Random factors have levels that are selected at random; whereas fixed factors have levels that are the only levels of interest. For example, you do a study on the effect of two levels of pressure on output measured by randomly chosen operators. Pressure is fixed (2 levels); and operator is random. The variance components output lists the estimated variance for the operator and error term. For more information on fixed and random factors, go to What is the difference between fixed and random factors?.