Step 1

Model specification with hypothesized population parameter values and employ a null covariance matrix ((i.e., a matrix with 1s on the diagonal and 0 s off the diagonal)

Step 2

Check of accuracy. The H1 model is freely estimated with the fitted covariance matrix from step 1 as input. If the estimated parameters estimated match those in Step 1, then we can proceed to the next step.

Step 3

Specification of H0. Select a sample size and specify a misspecified model by restricting the targeted parameterto zero (or the value expected under the null hypothesis), and then run the model using the generated covariance matrix as data input.

Step 4

Use the model chi-square from Step 3 as an approximate NCP to compute statistical power of detecting the effect of interest at a given a level

Step 5

Repeat Steps 3 and 4 with various sample sizes and compute corresponding

power values. The sample size corresponding to a power > 0.80 is an estimation of the required sample size.