Massachusetts_SGP_2024.R

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###          SGP analyses for 2024                                                               ###
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###   Load packages
require(SGP)
require(SGPmatrices)

###   Load data
load("Data/Massachusetts_SGP.Rdata")
load("Data/Massachusetts_Data_LONG_2024.Rdata")

###   Load configurations
source("SGP_CONFIG/2024/ELA.R")
source("SGP_CONFIG/2024/MATHEMATICS.R")

MA_CONFIG <- c(ELA_2024.config, MATHEMATICS_2024.config)

### Parameters
parallel.config <- list(BACKEND="PARALLEL", WORKERS=list(PERCENTILES=4, BASELINE_PERCENTILES=4, PROJECTIONS=4, LAGGED_PROJECTIONS=4, SGP_SCALE_SCORE_TARGETS=4))

###   Add Baseline matrices to SGPstateData
SGPstateData <- addBaselineMatrices("MA", "2024")

#  Establish required meta-data for STRAIGHT projection sequences
SGPstateData[["MA"]][["SGP_Configuration"]][["grade.projection.sequence"]] <- list(
    ELA=c(3, 4, 5, 6, 7, 8, 10),
    MATHEMATICS=c(3, 4, 5, 6, 7, 8, 10))
SGPstateData[["MA"]][["SGP_Configuration"]][["content_area.projection.sequence"]] <- list(
    ELA=rep("ELA", 7),
    MATHEMATICS=rep("MATHEMATICS", 7))
SGPstateData[["MA"]][["SGP_Configuration"]][["max.forward.projection.sequence"]] <- list(
    ELA=6,
    MATHEMATICS=6)

###   Run analysis

Massachusetts_SGP <- updateSGP(
        Massachusetts_SGP,
	Massachusetts_Data_LONG_2024,
        steps=c("prepareSGP", "analyzeSGP", "combineSGP", "outputSGP"),
        sgp.config=MA_CONFIG,
        sgp.percentiles=TRUE,
        sgp.projections=TRUE,
        sgp.projections.lagged=TRUE,
        sgp.percentiles.baseline=TRUE,
        sgp.projections.baseline=TRUE,
        sgp.projections.lagged.baseline=TRUE,
        sgp.target.scale.scores=TRUE,
        save.intermediate.results=FALSE,
        parallel.config=parallel.config
)

###   Save results
save(Massachusetts_SGP, file="Data/Massachusetts_SGP.Rdata")