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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:

  1. Channel – YouTube account the video was uploaded from
  2. Views – Number of times the video was viewed
  3. Comments_disabled – Whether the channel disabled other users from commenting on the video (no = comments enabled, yes = comments disabled)
  4. Theme – Category of the video (e.g. ‘Drama’, ‘Family’ etc)
  5. Weeks – Number of weeks available on YouTube to date
  6. 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?

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