Statistical growth plots (SGP) leverage longitudinal student assessment data to produce growth measures of students’ relative progress compared to their academic peers. SGPs compare a student’s current test score against a growth standard established using previous test scores and covariates (e.g. 75% of their academic peers). SGPs are a powerful measurement tool but require large estimation errors and complex calculations.

The SGP package contains several lower level functions (studentGrowthPercentiles, studentGrowthProjections) that can be used individually or in combination to perform a range of analyses. These functions can be combined with higher level wrapper functions (abcSGP, updateSGP) that simplify source code associated with operational analyses and provide additional functionality such as the ability to combine multiple student growth percentile estimates into a single report or to generate a growth projection for a given year. The SGP package also provides a number of additional tools that simplify the creation and management of SGP data sets such as sgpData, a streamlined way to store SGP state specific meta-data for use with the lower level SGP functions.

Students’ standardized test scores are compiled into a cumulative record that tracks their academic performance over time, typically in a single subject area, such as math. These records are then analyzed to determine the percentage of students that achieved proficiency in the subject area. This analysis requires converting raw student scores into scaled scores and then comparing these scaled scores to an average for the grade and subject. This information allows educators to see how their students are performing compared to other students in their class or the entire school and to identify areas for improvement.

SGP analyses utilize the least squares regression model and Bayesian inference to estimate latent achievement trait models for each student, and then compare these against growth standards that are typically established via teacher evaluation results. This comparison is important as it enables the identification of teachers that have an above or below average level of effectiveness in their classrooms, allowing educators to focus on those students who need the most help.

SGP programs analyze the growth trajectory of each student over time and report whether a student is above or below or at or around their state’s proficient standard. These reports can be incorporated into educator’s goal setting process and used to target student instruction and interventions. In addition, student-level SGPs can be shared with families and community members to provide them with a more complete picture of a student’s academic progression. This can help build trust with stakeholders and foster a culture of continuous improvement. The SGP package is designed to support these goals and includes extensive documentation, vignettes and examples that explain the calculations and processes involved in conducting these analyses. Educators are encouraged to familiarize themselves with these resources prior to starting SGP analyses and to contact support for assistance with their implementation.