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I have some data from an experiment that has 7 variables that have two levels to generate the conditions for the experiment. Consequently there are 128 (2^7) different combinations of variables. I've seen some data presented in lattice style panel plots that look good, but I've only come across ones that do this for 2 different variables. However, I was wondering if anyone had any ideas for presenting data where there are more than 2 variables (i.e. a contingency table doesn't work!)

I've provided some example data to explain what my data looks like if it wasn't clear:

cond1 <- c(1,2)
cond2 <- c(1,2)
cond3 <- c(1,2)
cond4 <- c(1,2)
cond5 <- c(1,2)
cond6 <- c(1,2)
cond7 <- c(1,2)
conditions <- expand.grid(cond1,cond2,cond3,cond4,cond5,cond6,cond7)
conditions <- sapply(conditions, rep.int, times=10)
data <- runif (nrow(conditions))
df1 <- cbind(conditions, data)
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You can still use a lattice by adding nested labels. If your software doesn't support nesting, you can make synthetic variables to simulate the nesting. For example, I think that would be cond123 = paste(cond1, cond2, cond3) in R.

The result can be a table of numbers or a graphical representation such as a heat map: enter image description here

This data is not completely random to show that some patterns can be noticed from this kind of display. I'll mark the formula as a spoiler in case you want to see what you can see from the images without knowing.

data value = random uniform(0, 1) + cond3 + cond4 + cond2 * cond5

If you're looking for particular patterns, you can use a graphical representation that will make those patterns more evident (at the expense of other patterns). For instance, a grid of one plot per variable will highlight any 1-dimensional effects.

enter image description here

And a grid of contour plots will highlight 2-dimensional effects. enter image description here Diagonal contours suggest some kind of combined effect.

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  • $\begingroup$ Presumably the spoiler code is SAS code. $\endgroup$ – Nick Cox Feb 25 '18 at 16:23
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    $\begingroup$ Yes, the function name is from the SAS JMP scripting language -- I was hoping it was be clear enough to serve as pseudo-code. And the graphs are made with JMP's Graph Builder feature. $\endgroup$ – xan Feb 25 '18 at 17:18
  • $\begingroup$ great, really nice plots! $\endgroup$ – unknown Feb 25 '18 at 23:59

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