Setting up Loops and Macros in Stata to Estimate Value-added Scores for Teacher Evaluations

Value-added models (VAM) are required by many states to hold teachers accountable for students’ growth within a certain period of time. For instance, the Florida Department of Education developed VAM for state-mandated assessments. Meanwhile, to evaluate teachers of subjects or grades not assessed by the state models, local districts in Florida started to build their own. However, with hundreds of locally-developed and/or statewide-administered standardized assessments, many districts found it difficult to develop systematic and efficient macros to run hundreds of statistical models and combine results. This presentation demonstrates a template to set up loops and macros in Stata that run a variety of linear regression models (single-level models with fixed effects, two-level, and three-level models with random effects) for the purpose of generating VAM-related statistics (e.g., point estimates, appropriate standard errors, performance levels, and model specification statistics) and save results in designated files. Specifically, in the case of single-level models, the presenter developed commands to make Stata compare the output results and automatically select the teacher with a median-sized effect as the reference for each model. By doing so no human judgement is involved during the looping process, thus making it time-efficient and void of human errors.