The data I am working on has multiple time points and multiple ligand effects. The data looks like this with percentage values in concentration being measured at each time point and ligand:
Sample Day ligand Condition Conc1 Conc2 .... Conc10 1 1 A Mild 99 86.6 .... 0.58 1 1 B Mild 96 85.4 .... 0.24 1 1 C Mild 92.56 88.23.... 0.22
There are 100 samples 1 through 100, three time points: day 1, 15 and 30; five ligands: A,B,C,D and E; two conditions: Mild and Severe.
I am trying to check for each
conc, if there is a significant difference between mild group and severe group. In addition to this, I also need to check for a significant difference in samples with respect to time points and lignads. I have several questions regarding the approach to follow:
Can I use a linear mixed model or a generalized linear mixed model or any other method since the response variable is in percentages?
If I use a linear mixed model, can I suppose ligands, day, and condition to be fixed effects and the sample to be a random effect?
Would there be any effect or variation between ligands?