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Massachusetts_SGP_2023.R
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Massachusetts_SGP_2023.R
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####################################################################################################
### ###
### SGP STRAIGHT BASELINE-REFERENCED projections for skip year SGP analyses for 2023 ###
### ###
####################################################################################################
### Load packages
require(SGP)
require(SGPmatrices)
### Load data
load("Data/Massachusetts_SGP.Rdata")
load("Data/Massachusetts_Data_LONG_2023.Rdata")
### Load configurations
source("SGP_CONFIG/2023/ELA.R")
source("SGP_CONFIG/2023/MATHEMATICS.R")
MA_CONFIG <- c(ELA_2023.config, MATHEMATICS_2023.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", "2023")
# Establish required meta-data for STRAIGHT projection sequences
SGPstateData[["MA"]][["SGP_Configuration"]][["grade.projection.sequence"]] <- list(
ELA_GRADE_3=c(3, 4, 5, 6, 7, 8, 10),
ELA_GRADE_4=c(3, 4, 5, 6, 7, 8, 10),
ELA_GRADE_5=c(3, 4, 5, 6, 7, 8, 10),
ELA_GRADE_6=c(3, 4, 5, 6, 7, 8, 10),
ELA_GRADE_7=c(3, 4, 5, 6, 7, 8, 10),
ELA_GRADE_8=c(3, 4, 5, 6, 7, 8, 10),
ELA_GRADE_10=c(3, 4, 5, 6, 7, 8, 10),
MATHEMATICS_GRADE_3=c(3, 4, 5, 6, 7, 8, 10),
MATHEMATICS_GRADE_4=c(3, 4, 5, 6, 7, 8, 10),
MATHEMATICS_GRADE_5=c(3, 4, 5, 6, 7, 8, 10),
MATHEMATICS_GRADE_6=c(3, 4, 5, 6, 7, 8, 10),
MATHEMATICS_GRADE_7=c(3, 4, 5, 6, 7, 8, 10),
MATHEMATICS_GRADE_8=c(3, 4, 5, 6, 7, 8, 10),
MATHEMATICS_GRADE_10=c(3, 4, 5, 6, 7, 8, 10))
SGPstateData[["MA"]][["SGP_Configuration"]][["content_area.projection.sequence"]] <- list(
ELA_GRADE_3=rep("ELA", 7),
ELA_GRADE_4=rep("ELA", 7),
ELA_GRADE_5=rep("ELA", 7),
ELA_GRADE_6=rep("ELA", 7),
ELA_GRADE_7=rep("ELA", 7),
ELA_GRADE_8=rep("ELA", 7),
ELA_GRADE_10=rep("ELA", 7),
MATHEMATICS_GRADE_3=rep("MATHEMATICS", 7),
MATHEMATICS_GRADE_4=rep("MATHEMATICS", 7),
MATHEMATICS_GRADE_5=rep("MATHEMATICS", 7),
MATHEMATICS_GRADE_6=rep("MATHEMATICS", 7),
MATHEMATICS_GRADE_7=rep("MATHEMATICS", 7),
MATHEMATICS_GRADE_8=rep("MATHEMATICS", 7),
MATHEMATICS_GRADE_10=rep("MATHEMATICS", 7))
SGPstateData[["MA"]][["SGP_Configuration"]][["max.forward.projection.sequence"]] <- list(
ELA_GRADE_3=6,
ELA_GRADE_4=6,
ELA_GRADE_5=6,
ELA_GRADE_6=6,
ELA_GRADE_7=6,
ELA_GRADE_8=6,
ELA_GRADE_10=6,
MATHEMATICS_GRADE_3=6,
MATHEMATICS_GRADE_4=6,
MATHEMATICS_GRADE_5=6,
MATHEMATICS_GRADE_6=6,
MATHEMATICS_GRADE_7=6,
MATHEMATICS_GRADE_8=6,
MATHEMATICS_GRADE_10=6)
### Run analysis
Massachusetts_SGP <- updateSGP(
Massachusetts_SGP,
Massachusetts_Data_LONG_2023,
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")