How to Use the SGP Package to Analyze Longitudinal Data
Whether you want to prepare your own data or simply find out how your students are doing, you can get the information you need through the SGPdata package. The package is designed to help you work with data in a LONG format. It also includes exemplar longitudinal data sets. There are a number of benefits to working with LONG data. First, you don’t have to worry about storage problems and you can spread out time-dependent data across multiple rows. In addition, most analyses are better off in a LONG format.
The SGP package assumes that you have access to state-specific meta-data. You can use this information to run student growth projections and analyze the scale score of individual students. For this reason, you will need to provide the sgpData table with unique student identifiers, first and last names, and grade level/time associated with assessment occurrences.
Next, you will need to provide the sgpData a set of columns that provides numeric scores for each year. If the data you have is missing, you will see a “missing” value, or NA, at the top of the sgpData table. When you use the summarizeSGP function to create an aggregated student score, you will need to supply these sgpData columns.
Finally, you will need to specify the scale score of your student, and the data you are using to analyze it. The sgpData table has five columns of assessment scores. Among the columns, the first contains the student’s unique identifier, and the second contains a set of numeric scores that are associated with the assessment occurrences. These scores are used to produce the student’s scale score. The student’s growth percentile is a number between one and 99. Depending on the size of the student’s state assessment score, the student’s growth percentile can vary a lot. Generally, a student with a low state assessment score shows high growth, while a student with a high state assessment score shows little or no growth.
You will also need to specify the CONTENT_AREA and YEAR fields in sgpData. Both are necessary for running the SGP package functions. You will also need to provide the VALID_CASE and GRADE fields, and the SCALE_SCORE field is needed for calculating individual level student growth plots.
With the above information, you can now access the site and start searching for the sgpData. The site will then display a table of the sgpData and show the NA values for those columns that don’t contain any data. This will enable you to view your student’s scale score easily and quickly.
Lastly, if you want to do more advanced analyses with your sgpData, you can make use of the SGP package’s comprehensive documentation. This includes information on sgpData’s WIDE and LONG formats and a wealth of exemplar longitudinal data sets. Ultimately, you can use the sgpData table to create your own student growth graphs. As a result of your analyses, you will have an accurate snapshot of your student’s achievement.