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; } } }

46037_en-US

liliconcom

How to determine the most appropriate model for a 2x2 factorial design, with three time points?

My Y variable is say "degradation of a certain compound x".

I have two independent variables with two levels in each, so that gives me 4 treatments. In each treatment, I have 18 replicates of a sample, and I am sampling 6 replicates at one time point.

3 time points in total.

I want to measure the differences between treatment combinations and time points. I have JMP Pro and would like to know which model fits most appropriately to my data set.

Re: How to determine the most appropriate model for a 2x2 factorial design, with three time points?

Since you are running JMP Pro, I suggest using the mixed model capability native to JMP Pro. Here's a link to the JMP online documentation for mixed modeling in JMP Pro. There are lots of examples and helpful hints.

http://www.jmp.com/support/help/13-2/Mixed_Models.shtml

Comments

There are no comments yet