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Aug 10, 2015 9:21 AM
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Aug 10, 2015 9:44 AM
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Aug 10, 2015 10:13 AM
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Aug 10, 2015 11:11 AM
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Aug 11, 2015 5:57 AM
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Aug 17, 2015 7:51 AM
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I would recommend that you do series of Y by X fit on each of the variable and see what the outputs give you. Bear in mind that depending on your data type (numeric,,,continuous, character...nominal, etc) the selected analysis that will be conducted will vary and that depends on your data type.

Jenkins Macedo

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Sep 1, 2015 10:36 AM
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There is useful information in the "biased" and "zeroed" messages. Lets say there are two terms in your model A and B (I know you are looking at 3-way interactions but this is just easier for explanation). If the 2 terms are collinear (aliased, correlated, take your pick of terminology) then statistically the effects of A and B can not be estimated independently of each other. This problem can be overcome by putting either A or B (but not both) in the model. Effectively this is what JMP is doing for you - if it puts A in the model and excludes B then A will be labelled as biased and B will be labelled as zeroed.

-Dave