PARCC Data Analysis 2015

Fall 2015 PARCC Consortium SGP Analyses

There were several end-of-course test (EOCT) and high school ELA course progressions from the Spring of 2015 to the Fall of 2015 that contained more than the 1,000 student minimum. These progressions were identified in the 2015_2016.1 configuration scripts, and the following R code was use to calculate the SGPs and establish an SGP object that would later be updated in the Spring 2016 analyses.

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###       SGP analysis script for PARCC consortium - Fall 2015 Analyses       ###
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workers <- parallel::detectCores()/2

### Load Packages

require(SGP)
require(RSQLite)
require(data.table)

###  Set working directory to PARCC/PARCC

### Load Data

parcc.db <- "./Data/PARCC_Data_LONG.sqlite"


###  Read in the Spring 2016 configuration code and combine into a single list.

source("../SGP_CONFIG/2015_2016.1/ELA.R")
source("../SGP_CONFIG/2015_2016.1/ELA_SS.R")
source("../SGP_CONFIG/2015_2016.1/MATHEMATICS.R")
source("../SGP_CONFIG/2015_2016.1/MATHEMATICS_SS.R")

PARCC_2015_2016.1.config <- c(
	ELA_2015_2016.1.config,
	ELA_SS_2015_2016.1.config,

	ALGEBRA_I.2015_2016.1.config,
	ALGEBRA_I_SS.2015_2016.1.config,
	ALGEBRA_II.2015_2016.1.config,
	ALGEBRA_II_SS.2015_2016.1.config,
	GEOMETRY.2015_2016.1.config,
	GEOMETRY_SS.2015_2016.1.config)


### abcSGP

PARCC_SGP <- abcSGP(
		state="PARCC",
		sgp_object=rbindlist(list(
			dbGetQuery(dbConnect(SQLite(), dbname = parcc.db), "select * from PARCC_Data_LONG_2015_2"),
			dbGetQuery(dbConnect(SQLite(), dbname = parcc.db), "select * from PARCC_Data_LONG_2016_1"))),
		sgp.config = PARCC_2015_2016.1.config,
		steps=c("prepareSGP", "analyzeSGP", "combineSGP", "outputSGP"),
		prepareSGP.create.additional.variables=FALSE,
		sgp.percentiles=TRUE,
		sgp.projections=FALSE,
		sgp.projections.lagged=FALSE,
		sgp.percentiles.baseline=FALSE,
		sgp.projections.baseline=FALSE,
		sgp.projections.lagged.baseline=FALSE,
		calculate.simex = TRUE,
		save.intermediate.results=FALSE,
		outputSGP.output.type=c("LONG_FINAL_YEAR_Data"),
        parallel.config=list(BACKEND="FOREACH", TYPE="doParallel", WORKERS=list(TAUS = workers, SIMEX=workers)))

###  Save object

save(PARCC_SGP, file="./Data/PARCC_SGP.Rdata")