• na random effects are due to A
 • na•nb random effects due to each nb B levels within A
 • na•nb•nw random effects due to each nw levels within B within A:
The Zs are the random effects for each level of the classification. Each Z is assumed to have a mean of zero and to be independent from all other random terms. The variance of the response y is the sum of the variances due to each z component:
Models Supported by the Variability Charts Platform shows the supported models and what the effects in the model would be.
 Model Factors Effects in the model Main Effects 1 2 unlimited A A, B and so on, for more factors Crossed 1 2 3 4 unlimited A A, B, A*B A, B, A*B, C, A*C, B*C, A*B*C A, B, A*B, C, A*C, B*C, A*B*C, D, A*D, B*D, A*B*D, C*D, A*C*D, B*C*D, A*B*C*D, and so on, for more factors Nested 1 2 3 4 unlimited A A, B(A) A, B(A), C(A,B) A, B(A), C(A,B), D(A,B,C) and so on, for more factors Crossed then Nested 3 A, B, A*B, C(A,B) Nested then Crossed 3 A, B(A), C, A*C, C*B(A)
The discrimination ratio compares the total variance of the measurement, M, with the variance of the measurement error, E. The discrimination ratio is computed for all main effects, including nested main effects. The discrimination ratio, D, is computed as follows:
P = estimated variance for a factor
T = estimated total variance