Multilevel Modeling Projects
This project use classroom.dta dataset provided by Professor Marc Scott.
The classroom dataset has three levels of nesting: schools, classrooms within schools and students within those classrooms. In this sample, there are 107 schools, a total of 312 classrooms across all schools, and 1190 students total. Within a school, there are between 2 and 31 students sampled.
| Variable Name | Label | ||
|---|---|---|---|
| Sex | Student Gender (0/1) | ||
| Minority | minority (0/1) | ||
| Mathkind | math score in spring of kindergarten | ||
| Mathgain | math score in spring of first grade | ||
| ses | ses | ||
| yearstea | Teachers’ years of teaching | ||
| mathknow | Teachers’ math knowledge | ||
| housepov | Average household poverty | ||
| mathprep | Teachers’ math prepartion (#courses) | ||
| classid | Class ID | ||
| schoolid | School ID | ||
| childid | Child ID |
This project starts with fitting an unconditional means model with school-specific random effects, which can be simply expressed as: