I realised a within-subject experiment and each participants went through three conditions and in each condition they performed a series of tasks of their choice (number of tasks is different for each participant, they have 8 minutes to do the tasks they want). Every time, I measure the time it takes them to perform each task within those 8 minutes.
I would like to build generalized mixed effect model to study the effect of random effects such as the tasks chosen. I only have one fixed effect which is the condition.
So I have the independent variable as condition and the dependent variable time.
After performing a Shapiro-Wilk test and looking at the histogram of my data, I see that it's not normally distributed and looks like a Poisson distribution.
Before I build a glmm to look at the random effects (tasks chosen, gender...etc), I decided to make a glm to see how it would look like just with condition as the fixed effect.
glm(Time ~ Condition, data = my_data, family = poisson(link = "log"))
I get this strange plot when I plot my glm model in R, I would be super grateful if anyone could give me a potential explanation of what it means. I was hoping to get scattered points all over the graph...
I haven't used lm or glm before, so I am trying to figure things out as I progress in the analysis. If you have any suggestion to improve my approach, please let me know !