Creation of lagged projections using lower level functions

Lagged_Projections.R

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### Creation of lagged projections using lower level functions
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### Update SGP & SGPdata packages to latest on GitHub

require(devtools)
install_github("centerforassessment/SGPdata")
install_github("centerforassessment/SGP")


### Load SGP package

require(SGP)
require(SGPdata)
require(grid)


### Set up for tests

my.sgpData <- list(Panel_Data=sgpData)


### student growth percentiles

my.grade.sequences <- list(3:4, 3:5, 3:6, 3:7, 4:8)

for (i in seq_along(my.grade.sequences)) {
        my.sgpData <- studentGrowthPercentiles(
                panel.data=my.sgpData,
                sgp.labels=list(my.year=2015, my.subject="Reading"),
                growth.levels="DEMO",
                goodness.of.fit="DEMO",
                grade.progression=my.grade.sequences[[i]],
                print.sgp.order=TRUE,
                verbose.output=TRUE,
                max.order.for.percentile=3,
                return.norm.group.scale.scores=TRUE)
}

### Create PDFs of all Goodness of Fit results:

for (i in names(my.sgpData$Goodness_of_Fit$READING.2015)) {
        pdf(file=paste(i, "_Reading_2015_GOF.pdf", sep=""), width=8.5, height=11)
                grid.draw(my.sgpData[["Goodness_of_Fit"]][["READING.2015"]][[i]])
        dev.off()
}


### student growth projections for lagged data

my.sgpData$Panel_Data <- sgpData[,c("ID", "GRADE_2011", "GRADE_2012", "GRADE_2013", "GRADE_2014", "SS_2011", "SS_2012", "SS_2013", "SS_2014")]
my.grade.progressions <- list(3, 3:4, 3:5, 3:6, 4:7)

for (i in seq_along(my.grade.progressions)) {
        my.sgpData <- studentGrowthProjections(
                panel.data=my.sgpData,
                sgp.labels=list(my.year=2015, my.subject="Reading", my.extra.label="LAGGED"),
                use.my.coefficient.matrices=list(my.year=2015, my.subject="Reading"),
                projcuts.digits=0,
                performance.level.cutscores="DEMO",
                percentile.trajectory.values=1:99,
                lag.increment=1,
                grade.progression=my.grade.progressions[[i]])
}