Power analysis in JMP

#1
Greetings,

I read through an example in the Minitab literature that shows how to analyze the power of factorial designs (shown below). Does anyone know if this type of analysis is possible in JMP verion 6?

Thanks,
Brian


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Example of calculating power for a two-level fractional factorial design

As a quality engineer, you need to determine the “best” settings for 4 input variables (factors) to improve the transparency of a plastic part. You have determined that a 4 factor, 8 run design (½ fraction) with 3 center points will allow you to estimate the effects you are interested in. Although you would like to perform as few replicates as possible, you must be able to detect effects of 5 or more. Previous experimentation suggests that 4.5 is a reasonable estimate of s.

1 Choose Stat ä Power and Sample Size ä 2-Level Factorial Design.
2 In Number of factors, enter 4.
3 In Number of corner points, enter 8.
4 In Replicates, enter 1 2 3 4.
5 In Effects, enter 5.
6 In Number of center points, enter 3.
7 In Sigma, enter 4.5. Click OK

--- Power and Sample Size ---

2-Level Factorial Design

Sigma = 4.5 Alpha = 0.05

Factors: 4 Base Design: 4, 8
Blocks: none

Including a term for center points in model.

Center
Points
Per Block Effect Reps Power
3 5 1 0.1577
3 5 2 0.5189
3 5 3 0.7305
3 5 4 0.8565

Interpreting the results

If you do not replicate your design (Reps = 1), you will only have a 16% chance of detecting effects that you have determined are important. If you use four replicates of your ½ fraction design for a total 32 runs, you will have an 86% chance of finding important effects
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