InstEval
(University Lecture/Instructor Evaluations by Students at ETH)
Data:
library(lme4)
data(InstEval)
Description:
University lecture evaluations by students at ETH Zurich, anonymized for privacy protection. This is an interesting “medium” sized example of a partially nested mixed effect model.
Format:
A data frame with 73421 observations on the following 7 variables.
s
- a factor with levels 1:2972 denoting individual students.
d
- a factor with 1128 levels from 1:2160, denoting individual professors or lecturers.
studage
- an ordered factor with levels 2 < 4 < 6 < 8, denoting student's “age” measured in the semester number the student has been enrolled.
lectage
- an ordered factor with 6 levels, 1 < 2 < ... < 6, measuring how many semesters back the lecture rated had taken place.
service
- a binary factor with levels 0 and 1; a lecture is a “service”, if held for a different department than the lecturer's main one.
dept
- a factor with 14 levels from 1:15, using a random code for the department of the lecture.
y
- a numeric vector of ratings of lectures by the students, using the discrete scale 1:5, with meanings of ‘poor’ to ‘very good’.
Each observation is one student's rating for a specific lecture (of one lecturer, during one semester in the past).
Details:
The main goal of the survey is to find “the best liked prof”, according to the lectures given. Statistical analysis of such data has been the basis for a (student) jury selecting the final winners.
The present data set has been anonymized and slightly simplified on purpose.
Task:
Model the ratings of lectures by the students.