Code to demonstrate that one can apply SGP analyses to tests like NAPLAN that occur bi-annually.

NAPLAN.R

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### Script to show use of SGP package with bi-annual assessment data like NAPLAN
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### Load SGP package

require(SGP)


### Need to modify meta-data in SGPstateData associated with state DEMO:

SGPstateData[["DEMO"]][["Growth"]][["System_Type"]] <- "Cohort Referenced"
SGPstateData[["DEMO"]][["Student_Report_Information"]][["Grades_Reported"]][["MATHEMATICS"]] <- c(4, 6, 8, 10)
SGPstateData[["DEMO"]][["Student_Report_Information"]][["Grades_Reported"]][["READING"]] <- c(4, 6, 8, 10)

SGPstateData[["DEMO"]][["Assessment_Program_Information"]][["Grades_Tested"]] <- c(4, 6, 8, 10)

SGPstateData[["DEMO"]][["Achievement"]][["Cutscores"]] <- list(
	MATHEMATICS=list(
		GRADE_4=c(383, 455, 538),
		GRADE_6=c(454, 520, 589),
		GRADE_8=c(521, 577, 628),
		GRADE_10=c(562, 627, 692)),
	READING=list(
		GRADE_4=c(517, 572, 671),
		GRADE_6=c(543, 600, 696),
		GRADE_8=c(578, 632, 724),
		GRADE_10=c(607, 663, 747)))


###  Create bi-annual data set from sgpData_LONG data object.

sgpData_LONG_BIANNUAL <- sgpData_LONG[!sgpData_LONG$GRADE %in% c(3,5,7,9),]


### prepareSGP

Demonstration_SGP <- prepareSGP(sgpData_LONG_BIANNUAL, state="DEMO", create.additional.variables=FALSE)


### analyzeSGP

Demonstration_SGP <- analyzeSGP(Demonstration_SGP, state="DEMO",
				sgp.percentiles=TRUE,
				sgp.projections=TRUE,
				sgp.projections.lagged=TRUE,
				sgp.percentiles.baseline=FALSE,
				sgp.projections.baseline=FALSE,
				sgp.projections.lagged.baseline=FALSE,
				simulate.sgps=FALSE)

### combineSGP

Demonstration_SGP <- combineSGP(Demonstration_SGP, state="DEMO")


### summarizeSGP

Demonstration_SGP <- summarizeSGP(Demonstration_SGP, state="DEMO")

### visualizeSGP

visualizeSGP(Demonstration_SGP,
		 state="DEMO",
 		 plot.types=c("bubblePlot","growthAchievementPlot"), # sgPlots can be produced, but they are UGLY (especially in 6th grade)!  Demo fails completely
 		 bPlot.styles=c(1),
 		 gaPlot.format="presentation",
 		 gaPlot.years="2011_2012", #parallel.config=list(BACKEND="FOREACH", TYPE=NA, WORKERS=list(GA_PLOTS=1, SG_PLOTS=1, SG_PLOTS_TARGETS=1)))
		 sgPlot.demo.report=TRUE) #  NOTE:  Turning this off will produce all plots for all students in the DEMO data