Week 9

#LMM example
  #data from 30 people
  #5 measurements on each person
  #the measurements on each person are going to be related to each other
  #create a random effect for each person

#2 main types of random effects
  #crossed random effects
    #i.e. students are nested within their teachers and teachers are nested in schools
  #nested random effects
    #i.e. speed dating where people interact, female and male random effects are crossed

#salamander example
  #random effect > 0 means more likely to mate
  #< 0 means less likely to mate

#test scores in school nested model
  #student random effect > 0 = student test scores are higher than class average
  #teacher random effect > 0 = their class's test scores are higher than the school average

#speed dating - response is whether you want to see someone again
  #rater random effect > 0 - they want to see more people again / are interested in many people
  #person being judged random effect> 0 - more people want to see them again / lots of people are interested in them