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Melvin Stephens

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Statistics back end for Gates evalaution engine - Supplement

a PSC Research Project

Investigator:   Ben Hansen

Many educational interventions can be evaluated informatively by comparing administrative outcomes of intervention-group students to those of comparison groups consisting of similar students. If similarity is understood in terms of variables available to state educational agencies, so that the evaluation is to be driven by comparisons among students matched on administrative variables, then evaluations of this kind ought to be simple to perform; in practice, however, gaining access to these legally protected databases is costly and time consuming, and may require masking of some of the data. The Gates Foundation's Evaluation Engine will drastically streamline the process of performing matched comparisons using administrative education data by presenting a web-interface, database and statistical analysis program enabling researchers to conduct statistical analyses on FERPA-protected data that they have no direct access to. This project develops and contributes an important component of the Gates Evaluation Engine, the programs and routines it uses to prepare and present statistical analyses.
In a typical Evaluation Engine usage scenario, the researcher presents student identifiers for an intervention group enrolled in schools in a given state. Then the Evaluation Engine identifies the students within a protected state database, finds comparable students not belonging to the intervention group from within that same states database, and performs a suitable statistical analysis comparing outcomes among the intervention group students and the comparison group students. Results of this analysis are then presented to the researcher in an automatically generated report.

This project consists of developing statistical methods and software for the specifically statistical aspects of these Evaluation Engine tasks, namely: assembling, preparing and periodically updating the state databases; in real time finding suitable matches for the members of an intervention group from among the complementary collection of students within the same state; validating collections of matches in ways that are intelligible and useful to researchers; comparing intervention subjects and their matched controls for overall differences (on outcome measures appearing in the database) and for selected subgroup differences, with appropriate adjustment for residual differences left by the matching procedure.

Many educational interventions can be evaluated informatively by comparing administrative outcomes of intervention-group students to those of comparison groups consisting of similar students. If similarity is understood in terms of variables available to state educational agencies, so that the evaluation is to be driven by comparisons among students matched on administrative variables, then evaluations of this kind ought to be simple to perform; in practice, however, gaining access to these legally protected databases is costly and time consuming, and may require masking of some of the data. The Gates Foundation's Evaluation Engine will drastically streamline the process of performing matched comparisons using administrative education data by presenting a web-interface, database and statistical analysis program enabling researchers to conduct statistical analyses on FERPA-protected data that they have no direct access to. This project develops and contributes an important component of the Gates Evaluation Engine, the programs and routines it uses to prepare and present statistical analyses.
In a typical Evaluation Engine usage scenario, the researcher presents student identifiers for an intervention group enrolled in schools in a given state. Then the Evaluation Engine identifies the students within a protected state database, finds comparable students not belonging to the intervention group from within that same states database, and performs a suitable statistical analysis comparing outcomes among the intervention group students and the comparison gr

Funding Period: 07/01/2013 to 12/31/2013

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