You can use the output of the cld function as data frame.  It gives you the ls means and the confidence intervals for each treatment combination.

I have some examples in http://rcompanion.org/handbook/ , but there's not a perfect one for this case.  I'll try to mock one up quickly.

Hi Salvatore,

lsmeans function gives me lsmeans and SEM, I am OK with that step. Interaction plot gives interaction plots, I am also OK with that step but how to use that lsmeans and SEM to make graphs or use in interaction plots in R, any suggestions please? Would appreciate,

R code for producing an interaction plot from the lsmeans output can be found at the following link.

http://rcompanion.org/handbook/G_06.html#plot

Perfect, will look at it and may come back if there is anything. Thanks a lot, appreciated!!

There is R code on p. 67 of the book in the link to draw the plot. Best wishes, David

https://www.amazon.com/Analysis-Experiments-Chapman-Statistical-Science/dp/1439868131/ref=sr_1_1?ie=UTF8&qid=1487410817&sr=8-1&keywords=john+lawson+r

Get a look to this:

https://cran.r-project.org/web/packages/phia/vignettes/phia.pdf

Cheers!

I found my script ;)

#--------------------------------

refR

Hi Marianna, Thanks! Do you also have R codes to calculate AUC from time series data?

Hi!

No, I am sorry. I am not working with that kind of data frame...

Good luck!

You can use the ggeffects-package (https://cran.r-project.org/package=ggeffects) or sjPlot-package (https://cran.r-project.org/package=sjPlot) to plot marginal effects / least square means of models with interaction terms.

See the related vignettes for examples:

https://cran.r-project.org/web/packages/ggeffects/vignettes/marginaleffects.html

https://cran.r-project.org/web/packages/sjPlot/index.html

Great Daniel! Thank you.