I study comparative biology and have been trying to estimate ancestral character states for continuous characters using the package phytools.

The optimization of the characters is perfect but I have problems editing the outcome image. My main goal is that all the branches have the same length, right now I am getting random lengths as in the attached image.

Here's the code I'm using:

obj<-contMap(tree, cont.charac, plot=FALSE)

plot(obj,legend=0.7*max(nodeHeights(tree)))

I have tried using the argument "use.edge.length = FALSE" with no success. And have also tried other commands as "plot.phylo" and "plotTree", for which I got the error message: found less than 2 tips in the tree.

Thanks a lot for your consideration.

Best regards,

jessica

I am practicing on these data I have and I want to apply a statistical test.

I want to compare 2 treatments: evolution and incidence of a certain disease after treatment.

There were 3 groups taken into study: treated with A (n=78), treated with B (n=65) and C=control group, untreated (n=72).

I evaluated them initially, 6 months and 12 months after the initiation of treatment. Each subject received score 0, 1 or 2 at these time points.

Since the data are categorical, I am thinking of applying chi-square test, but I am not quite sure about the steps I have to follow.

Should I calculate expected value (and how?), the distribution of the data (?). Could you suggest some steps (mean, standard deviation)? Thank you!

We have for example an MRI after 6 months, 1 year, 2 year, 3 year, 4 year etc....

We compare the MRI of 6 months with that of 1 year, that of 1 year with that of 2 year etc...

Serial comparisons .... We do this with both imaging rating methods. We have two longitudinal sets of serial comparisons.

Now we want to compare those two longitudinal serial comparisons with each other and prove which of two imaging rating methods detects growth faster or more accurate than the other one.

Also we want to look which methods best predicts outcome.

When reading literature it does not become clear which tests to use.

we would be very grateful if anyone can help. ]]>