The SGP package has a suite of functions that enable data analyses and updates. Its functions use WIDE and LONG formats. In addition, it requires identification of student, year, state, and content area to conduct its analyses. These and other variables are required for all SGP analyses. For example, the summarizeSGP function creates student aggregates, and the GRADE and SCALE_SCORE functions run student growth plots.
A LONG format is a type of longitudinal student assessment data, spreading time dependent data across multiple rows. This is beneficial for numerous preparation and storage reasons. However, a LONG format also requires 7 required variables. One of these is ID, which is the unique student identifier. Another is ACHIEVEMENT_LEVEL, which is needed for running student growth projections. There is also the requirement of LAST_NAME, which is used for individual level student growth plots.
For most analyses, a LONG format is preferred. Because the data are spread out over multiple rows, the columns represent variables associated with a student at different times. This is done for both longitudinal and annual assessments. Additionally, a LONG format has storage benefits because the columns are smaller than those in the WIDE format. If you are considering conducting an SGP analysis, a LONG format is probably the best format to use.
As mentioned earlier, a LONG format is preferred for most analyses, because it is more suited for a wide range of purposes. While there are some scenarios where a WIDE format might be preferred, many SGP analyses are based on a LONG format. Thus, it is important to understand which one you are working with.
The sgpData table represents a five-year, panel-based assessment data set. The first column contains a unique student identifier and the next 5 columns contain the scale scores for each year. Each of these columns is associated with a grade level and a time period. Any missing values (NA) are displayed.
The SGP package provides extensive documentation on sgpData. You can access this information via the package’s website. Several exemplar longitudinal data sets are also available. Using the information provided, you can learn more about the sgpData data set and the methods for using it.
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