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- Power calculations for categorical variables.

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Jul 8, 2015 7:24 AM
(4349 views)

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.

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Jul 8, 2015 2:47 PM
(8178 views)

Solution

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!

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Jul 8, 2015 2:47 PM
(8179 views)

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!

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Jul 8, 2015 3:26 PM
(4089 views)

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?

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Jul 8, 2015 3:30 PM
(4089 views)

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Jul 9, 2015 1:24 PM
(4089 views)

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?