Data sgp is an exemplar data set which models the format of the data used with the lower level functions studentGrowthPercentiles and studentGrowthProjections. It is an anonymized panel data set of 5 years of annual, vertically scaled assessment data. The data sgp consists of a set of teacher-student relationships with associated assessment occurrences and numeric scores.
The data sgp is a comprehensive set of assessment data available to researchers. It includes a large number of standardized tests, performance tasks, and other forms of evidence from both public and private schools. In addition, the data sgp also contains a wide variety of contextual and socioeconomic indicators. It is available in many formats and can be accessed by researchers from any location.
As with any data, it is important to be careful in preparation and to avoid errors that can tamper with results. The vast majority of errors that occur when running SGP analyses revert back to problems with the data preparation. Thus, SGP analyses are very straightforward and require minimal effort once proper data preparation is complete.
If you are new to SGP, we recommend that you read the documentation carefully before attempting any analyses. Once you have a good grasp of the data structure and syntax, the analyses themselves should be no problem.
In addition, if you encounter any problems while running an analysis, we suggest that you first try to resolve the problem with the help of the SGP support community. This can often be done by submitting an issue on the GitHub repository.
SGP provides a very powerful set of tools for measuring student growth and development. The tools include a range of statistical models, including regression and growth modeling. These methods allow researchers to examine student achievement over time and to assess the effects of school-level policies on student performance.
The SGP package is designed to be flexible, allowing users to conduct SGP analyses in a variety of ways. The lower level functions (studentGrowthPercentiles and studentGrowthProjections) require WIDE formatted data, whereas the higher level wrapper functions, abcSGP and updateSGP, utilize LONG formatted data. For operational SGP analyses, we recommend that users format their data in the LONG format as this offers many preparation and storage benefits over WIDE data.
SGP analyses should always be conducted on an operational basis and not on a per-student basis. This is because the statistical methods used in SGP can produce very conservative estimates of student achievement if the data is not analyzed using the proper methodology. It is important that each district or school prepares a consistent and standard procedure for SGP analyses, and trains teachers in this methodology before conducting any operational SGP analyses. This will ensure that the results are as accurate and useful as possible. The SGP package is designed to provide support for this by providing the necessary infrastructure, such as a standard data format and a common method for describing the data and generating reports.