As with most data analyses, SGP analyses require extensive preparation before they can begin. Once data are ready to use, however, SGP analyses become relatively straightforward and simple – especially since the SGP package provides tools to facilitate various forms of analysis. It is strongly suggested that users familiarise themselves with its documentation prior to engaging with it.

SGP analyses typically follow a straightforward path. Any discrepancies that arise usually stem from improper data preparation; we thus stress the importance of dedicating most of one’s effort towards this effort.

Typically, lower level functions (studentGrowthPercentiles and studentGrowthProjections) require WIDE formatted data, while wrappers for these lower level functions allow LONG formatted data as an option. Your decision of WIDE or LONG data depends upon your unique requirements as well as how much data needs to be analyzed.

The first column in sgpData, identified by its name alone identifier, serves to uniquely identify students in each year of assessment. GRADE_2013, GRADE_2014, GRADE_2015 and GRADE_2016 provide grade levels associated with test scores across years 1 through 5, while the remaining four provide scale scores associated with each student over this timeframe.

SGPs are determined by comparing students’ current performance against that of their academic peers from prior MCAS administrations, so two students with similar scaled score histories could have the same SGP even though they currently score differently across content areas.

An annual average SGP is calculated by aggregating all students who have taken at least one test in each of the 3 assessment windows used to calculate SGPs. These statewide average SGPs can then be used to generate growth estimates for schools, districts, or subgroups within schools or districts.

While statewide median SGPs remain constant at 50, their exact values may fluctuate slightly year to year due to changes in norms or slight misfit. Statewide average SGPs provide an indicator of school or district growth rates but do not give information on individual student performance.

As well as statewide aggregate SGP graphs, the SGP package offers various data visualizations to aid in understanding trends in student growth across schools or districts. These include graphs that display mean SGPs by demographic group as well as bubble plots which show what percentage of the student population was proficient or advanced on each statewide assessment during each assessment window – perfect tools to determine where improvement efforts must be directed for achievement gaps evaluation purposes.