PARCC/PARCC_SGP_Baseline_2019_2020.2.R at master · CenterForAssessment/PARCC · GitHub

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################################################################################
###                                                                          ###
###      PARCC 2020 Baseline Growth Percentiles and Projections Analyses     ###
###                                                                          ###
################################################################################

###   Load packages
require(SGP)
require(data.table)

###   Load data from 2019 baseline SGP analyses
load("./Data/Archive/2018_2019.2/BASELINE/PARCC_SGP.Rdata")
PARCC_SGP@Data <- PARCC_SGP@Data[YEAR > "2016_2017.2"]

###   Load 2020 Data available from Illinois before schools closed down...
load("../Illinois/Data/Archive/2019_2020.2/Illinois_Data_LONG_2019_2020.2.Rdata")

###   Add single-cohort baseline matrices to SGPstateData
load("./Data/PARCC_Baseline_Matrices.Rdata")
SGPstateData[["PARCC"]][["Baseline_splineMatrix"]][["Coefficient_Matrices"]] <- PARCC_Baseline_Matrices

###   Read in BASELINE projections configuration scripts and combine
source("./SGP_CONFIG/2019_2020.2/ELA.R")
source("./SGP_CONFIG/2019_2020.2/MATHEMATICS.R")

PARCC_2019_2020_CONFIG <- c(
	ELA_2019_2020.2.config,
	MATHEMATICS_2019_2020.2.config
)

#####
###   Run projections analysis
#####

###   Baseline Percentiles (Step B)

PARCC_SGP <- updateSGP(
        what_sgp_object = PARCC_SGP,
				with_sgp_data_LONG = Illinois_Data_LONG_2019_2020.2,
        steps = c("prepareSGP", "analyzeSGP", "combineSGP", "outputSGP"),
        sgp.config = PARCC_2019_2020_CONFIG,
        sgp.percentiles = FALSE,
        sgp.projections = FALSE,
        sgp.projections.lagged = FALSE,
        sgp.percentiles.baseline = TRUE,
        sgp.projections.baseline = FALSE,
        sgp.projections.lagged.baseline = FALSE,
        save.intermediate.results = FALSE,
				outputSGP.output.type=c("LONG_Data", "LONG_FINAL_YEAR_Data"),
				outputSGP.directory="PARCC/Data/Archive/2019_2020.2",
        parallel.config = list(
					BACKEND = "PARALLEL",
          WORKERS=list(BASELINE_PERCENTILES=8))
)


###   Baseline Projections (Step C)
###   (in case need P50_PROJ_YEAR_1_CURRENT for Ho's Fair Trend/Equity Check metrics)

SGPstateData[["PARCC"]][["SGP_Configuration"]][['sgp.projections.max.forward.progression.years']] <- 1
SGPstateData[["PARCC"]][['SGP_Configuration']][['max.sgp.target.years.forward']] <- 1

PARCC_SGP <- abcSGP(
        sgp_object = PARCC_SGP,
        steps = c("prepareSGP", "analyzeSGP"),
        sgp.config = PARCC_2019_2020_CONFIG,
        sgp.percentiles = FALSE,
        sgp.projections = FALSE,
        sgp.projections.lagged = FALSE,
        sgp.percentiles.baseline = FALSE,
        sgp.projections.baseline = TRUE,
        sgp.projections.lagged.baseline = FALSE,
        save.intermediate.results = FALSE,
        parallel.config = list(
					BACKEND = "PARALLEL",
          WORKERS=list(PROJECTIONS=8))
)

###   Save results
save(PARCC_SGP, file="./Data/Archive/2019_2020.2/PARCC_SGP.Rdata")