Stuck on confidence interval analysis for GLM

I'm really new to R, and sort of stats in general.

I've been using a GLM to analyse a series of data, which is basically tracking how concentrations of DNA change over time, when different treatments are applied (temperature).

Here is what I have so far, I just don't really know what to do next. I believe I try to plot the confidence intervals, and then each treatment over time?

If this is the case, can anyone help me with the code to plot what I need?

Apologies for the vague question, and thanks for your help.

• I guess that you are trying to find the optimal treatment and time of treatment? Why not plot the data points as function of time and give them different colour? Then fit some appropriate curves through the data and use those curves to define the optimum. You may possibly need no glm for this and you can the simpler linear least squares model by using the function lm (GLM is, as the names says, more general, and has more options which you probably won't need and may only confuse you). – Sextus Empiricus May 27 at 7:07
• See here for more and better help on programming with R: stats.meta.stackexchange.com/a/795/164061 – Sextus Empiricus May 27 at 7:11
• Hi Sextus, thanks for your help. I'm actually just trying to compare treatments, and see if there is a significant difference between the three temperatures. I used a GLM as I have three treatments, a continuous response variable, and I'm measuring time points. I may have done it wrong though – Bio1211 May 27 at 13:11