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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: