The SGP package is a set of functions that are designed to use LONG format data. This type of data is longitudinal student assessment data, spread out over multiple rows. It has a number of benefits for analysis and storage. In addition to these benefits, most analyses are better suited for LONG data.
One of the primary reasons for using a LONG format is to support analysis of student growth. For example, a student with a high state assessment score might show low growth. However, a student with a very low state assessment score might show very high growth. These differences can be observed by creating student growth plots.
If you are interested in a student’s individual level growth plot, you will need to provide a unique student identifier (ID). The first column in the sgpData table must contain the ID. Next, you will need to provide the grade level and time associated with each assessment occurrence. You will also need to provide a numeric score for each assessment occurrence.
Similarly, if you are going to run student growth projections, you will need to provide the following variables: SCALE_SCORE, ACHIEVEMENT_LEVEL, GRADE, CONTENT_AREA, FIRST_NAME, and VALID_CASE. All of these variables are demographic variables that are used for creation of student aggregates by the summarizeSGP function.
There are also a number of exemplar longitudinal data sets that you can download from the SGP package. Each of these exemplars will provide you with a full year of annual assessment data. Once you have downloaded the data, you can analyze and compare it to the student’s actual results.
Additionally, the SGP package has several functions that are available to help you interpret and utilize your data. These functions can help you construct a number of different types of student growth plots. You will also find a detailed documentation of sgpData in the SGP package, which should prove useful to you as you conduct analyses.
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