InstEval {lme4} | R Documentation

## University Lecture/Instructor Evaluations by Students at ETH

### 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.

### Examples

    str(InstEval)

    head(InstEval, 16)
    xtabs(~ service + dept, InstEval)

[Package lme4 version 1.1-11 Index]