Hello,
I'm analyzing bray-curtis values over time. I would like to quantify if 1) there is a rapid or gradual change in bray curtis values, and 2) how long this change occurs. As a hypothetical example, Fig. 1a, a rapid increase until sampling week four. Is there a trend analysis I could run that would allow me to use terminology such as 'gradual' or 'rapid' based on slope? Or something along those lines.
I primarily use R.
Thank you.
Josh
Did you already think about using regression analysis with time as explanatory variable? Than you could use the slope as an indicator of increase (or decrease). Of course normally you would transform your data in order to linearize your relationship (between time and BC). But then you would capture the general trend (over 19 weeks) in your model and not the different parts in your trend (as you describe in fig. 1a
Is it necessary to quantify the changes? Can't you just qualitatively describe the changes?
Koenraad Van Meerbeek I think that may be the best bet. Thanks for your insite. I think what I'm going to do is a segmented regression. Calculate the breakpoint, and get a best fit line for which ever weeks increase until the breakpoint. I found a function called 'segmented' in R that does this.
- Badges
- Science topic
- Similar topics
- Theoretical Physics
- Time