My data is like the below table:
username Tweet_id Agegroup Time Score A unique Young 1 0.2 A unique Young 2 0.3 B unique Old 1 0.5 c unique Old 4 0.6
Each user(username) may post between one and many tweets, and each tweet(tweet_id) was posted in different times(Time) and has a different score (Score).
I hope to examine the effect of time and age(also an interaction) on Score.
My guess is that tweetid should be nested in the username like a class nested in the school.
I am not sure if I am building up a correct linear mixed model. Since I have a million row, how I can speed up the test. Also, How can I generate linear mixed model tables and plot(better to have an interaction plot between age and Time)
lm1 = lmer(score~ 1+agegroup+Time+ (1|username/Tweet_id),data = new_data,control = lmerControl(calc.derivs = FALSE))