SGP (version 0.7-1.0)

analyzeSGP: Analyze student data to produce student growth percentiles and student growth projections

Description

Utility function/exemplar used to produce student growth percentiles and student growth projections using long formatted data like that provided by prepareSGP.

Usage

analyzeSGP(sgp_object,
         state,
         years,
         content_areas,
         grades,
         sgp.percentiles=TRUE,
         sgp.projections=TRUE,
         sgp.projections.lagged=TRUE,
         sgp.percentiles.baseline=TRUE,
         sgp.projections.baseline=TRUE,
         sgp.projections.lagged.baseline=TRUE, 
         simulate.sgps=TRUE,
         goodness.of.fit.print=TRUE,
         sgp.config,
         sgp.baseline.config,
         parallel.config,
         ...)

Arguments

sgp_object

An object of class SGP containing long formatted data in the code (from prepareSGP) slot.

state

Acronym indicating state associated with the data for access to embedded knot and boundaries, cutscores, CSEMs, and other state related assessment data.

years

A vector indicating year(s) in which to produce student growth percentiles and/or student growth projections/trajectories. If missing the function will use the data to infer the year(s) based upon the assumption of having at least three years of panel da

content_areas

A vector indicating content area(s) in which to produce student growth percentiles and/or student growth projections/trajectories. If left missing the function will use the data to infer the content area(s) available for analyses.

grades

A vector indicating grades for which to calculate student growth percentiles and/or student growth projections/trajectories. If left missing the function will use the data to infer all the grade progressions for student growth percentile and student grow

sgp.percentiles

Boolean variable indicating whether to calculate student growth percentiles. Defaults to TRUE.

sgp.projections

Boolean variable indicating whether to calculate student growth projections. Defaults to TRUE.

sgp.projections.lagged

Boolean variable indicating whether to calculate lagged student growth projections often used for growth to standard analyses. Defaults to TRUE.

sgp.percentiles.baseline

Boolean variable indicating whether to calculate baseline student growth percentiles and/or coefficient matrices. Defaults to FALSE.

sgp.projections.baseline

Boolean variable indicating whether to calculate baseline student growth projections. Defaults to FALSE.

sgp.projections.lagged.baseline

Boolean variable indicating whether to calculate lagged baseline student growth projections. Defaults to FALSE.

simulate.sgps

Boolean variable indicating whether to simulate SGP values for students based on test-specific Conditional Standard Errors of Measurement (CSEM). Test CSEM data must be available for simulation and included in stat

goodness.of.fit.print

Boolean variable indicating whether to print out Goodness of Fit figures as pdf into a directory labeled Goodness of Fit. Defaults to TRUE.

sgp.config

If years, content_areas, and grades are missing, user can directly specify a list containing three vectors: baseline.content.areas, baseline.panel.years, and baseline.grade.sequences

sgp.baseline.config

If years, content_areas, and grades are missing, user can directly specify a list containing four vectors: sgp.content.areas, sgp.panel.years, sgp.grade.sequences, and bas

parallel.config

A named list indicating, at a minimum, the TYPE of the back end to be used for parallel computation. TYPE = one of FOREACH, SNOW, MULTICORE. List may also contain WORKERS for the number of cores or nodes used in

...

Arguments to be passed to studentGrowthPercentiles or studentGrowthProjections for finer control over SGP calculations. NOT

Value

• Function returns a list containing the long data set in the Data slot as a data.table keyed using VALID_CASE, CONTENT_AREA, YEAR, ID and the student growth percentile and/or student growth projection/trajectory results in the SGP slot.

See Also

prepareSGP, combineSGP

Examples

Run this code

## analyzeSGP is Step 2 of 5 of abcSGP
Demonstration_Data <- sgpData_LONG
Demonstration_Data <- prepareSGP(Demonstration_Data)
Demonstration_Data <- analyzeSGP(Demonstration_Data)

## Or (explictely pass state argument)

Demonstration_Data <- prepareSGP(sgpData_LONG)
Demonstration_Data <- analyzeSGP(Demonstration_Data, state="DEMO")

Run the code above in your browser using DataLab