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Idaho_SGP_2019_PART_A.R
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Idaho_SGP_2019_PART_A.R
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#########################################################################
### ###
### Idaho Learning Loss Analyses -- Create Baseline Matrices ###
### ###
#########################################################################
### Load necessary packages
require(SGP)
### Load Data
load("Data/Idaho_SGP.Rdata")
load("Data/Idaho_Data_LONG_2019.Rdata")
### Create a smaller subset of the LONG data to work with.
Idaho_SGP_LONG_Data <- updateSGP(Idaho_SGP, Idaho_Data_LONG_2019, steps="prepareSGP")@Data
Idaho_Baseline_Data <- data.table::data.table(Idaho_SGP_LONG_Data[, c("ID", "CONTENT_AREA", "YEAR", "GRADE", "SCALE_SCORE", "ACHIEVEMENT_LEVEL", "VALID_CASE"),])
### Read in Baseline SGP Configuration Scripts and Combine
source("SGP_CONFIG/2019/Matrices/ELA.R")
source("SGP_CONFIG/2019/Matrices/MATHEMATICS.R")
Idaho_BASELINE_CONFIG <- c(ELA_BASELINE.config, MATHEMATICS_BASELINE.config)
### Create Baseline Matrices
Idaho_SGP <- prepareSGP(Idaho_Baseline_Data, create.additional.variables=FALSE)
Idaho_Baseline_Matrices <- baselineSGP(
Idaho_SGP,
sgp.baseline.config=Idaho_BASELINE_CONFIG,
return.matrices.only=TRUE,
calculate.baseline.sgps=FALSE,
goodness.of.fit.print=FALSE,
parallel.config = list(
BACKEND="PARALLEL", WORKERS=list(TAUS=4))
)
### Save results
save(Idaho_Baseline_Matrices, file="Data/Idaho_Baseline_Matrices.Rdata")