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Jul 25, 2013 9:23 PM
(3967 views)

Hi,

I am having a data set with blocking factor, whole plot, and split plot factors. I want to use fit model in JMP. I read some stuff online and figured out for whole plot I need to specify it as "random effect", but couldn't find anything regarding the blocking factor. How I tell fit model in JMP that a factor is a blocking factor?

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I'm not sure if you are saying that you have a blocking factor and a whole plot factor, or just a whole plot factor. Either way, it's most common that the blocking factor acts as a random effect - so you select the term in your model specification then choose random effect from the attributes option. You'll find more details under Help>Books>Modeling and Multivatiate Methods ... just do a search for split-plot

-Dave

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I'm not sure if you are saying that you have a blocking factor and a whole plot factor, or just a whole plot factor. Either way, it's most common that the blocking factor acts as a random effect - so you select the term in your model specification then choose random effect from the attributes option. You'll find more details under Help>Books>Modeling and Multivatiate Methods ... just do a search for split-plot

-Dave

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Re: block and split-plot analysis by "fit model"

Jul 26, 2013 8:45 AM
(3730 views)
| Posted in reply to message from David_Burnham 07/26/2013 11:35 AM

I actually have both.

So, does this mean if the blocking factor is not random, we don't need to specify anything for the blocking factor different from other factors. so what is the difference between a blocking factor and a normal factor when fitting a model?