nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

Power calculations for categorical variables.

unknown

Can someone please explain how JMP calculates statistical power associated with the individual levels and the whole effect of a categorical variable? I know the equations used for calculating power in case of a continuous variable but they don't seem to work in the case of categorical variables.

Accepted answers

jules

Hi agn3284,

It sounds like you're calculating power with DOE > Sample Size and Power > K Sample Means, is that correct? The power calculated there is for the overall, omnibus ANOVA only. Pairwise tests have to be considered separately. Here is a link to some of the technical details for that calculation: Technical Details. Scroll down to "Power for a Categorical Effect."

To calculate power for pairwise companions you would need to use "Two Sample Means" rather than K sample means. Be sure to consider any of the alpha control procedures you'll be using when calculating prospective power.

I hope this helps!

julian

All comments

jules

Hi agn3284,

I hope this helps!

julian

unknown

Hi Julian,

Thanks for the answer. I created a design using the custom design option consisting of just 1 categorical variable with 3 levels and N = 6 runs. I used the DOE> Evaluate Design option to look at the power values. Will the calculations be the same for those power values?

jules

Hi agn3284,

Yes, that will use the same calculations for power.

julian

unknown

Hi Julian,

The answer was very helpful but I am a little confused on how to get the L matrix. I took the anticipated betas as 1 and -1 for levels 1 and 2 respectively. Can you please explain how to get the L matrix?