I did a survey-experiment for my master's thesis. My supervisor has recommended that I use GLM due to design having mixed components (the treatments are fixed but the participants and the pictures included on the survey are random) but I am finding it hard to interpret the results.

On the survey the participants randomly got into one out of 3 conditions. Then they saw 10 pictures and had to answer 6 questions for each picture. Depending on the treatment the picture either included a sign type 1, type 2 or no sign. They answered the questions on a five-point likert scale.

For this model I used the average for the 10 pictures that each participant answered for a specific question, this was recommended to me but also this model shows a lower AIC than the others I have tried.

The variables used are:

NN vs N - NN is represented by 0 and it means that the picture picture or treatment did not include a sign. N represents it had a sign.

Treatment - 0 represents it did not include a sign. 1 that it included a sign type 1 and 2 that it included a sign type 2.

I would really appreciate it if somebody could help me understand the results.