I'm unconfident that whether my understanding on fixed effect and random effect is correct:
Fixed effect= variable that make inferences about the specific levels.
Random effect= variable that make inferences about and generalise to a wider population.
Now I have 6 variables in my glm model:
- Channel – YouTube account the video was uploaded from
- Views – Number of times the video was viewed
- Comments_disabled – Whether the channel disabled other users from commenting on the video (no = comments enabled, yes = comments disabled)
- Theme – Category of the video (e.g. ‘Drama’, ‘Family’ etc)
- Weeks – Number of weeks available on YouTube to date
- Tags – Number of tags, key words assigned to the video that users can search for within YouTube
I defined them as:
Fixed effect: 2
Random effect: 1, 3, 4, 5, 6
Am I correct?