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Colorado_SGP_2022.R
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138 lines (112 loc) · 4.81 KB
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##############################################################################
### ###
### Colorado 2022 Cohort and Baseline SGP analyses ###
### * Includes 2019 consecutive-year baselines * ###
### ###
##############################################################################
### Load packages
require(SGP)
require(data.table)
### Load data
load("Data/Colorado_SGP.Rdata")
### Add baseline matrices to `SGPstateData`
SGPstateData <- SGPmatrices::addBaselineMatrices("CO", "2021")
SGPstateData[["CO"]][["Assessment_Program_Information"]][["CSEM"]] <- NULL
#####
### PART A -- 2019 Consecutive Year Baseline SGPs
#####
### Rename the skip-year SGP variables and objects
## We can simply rename the BASELINE variables. We only have 2019/21 skip yr
# table(Colorado_SGP@Data[!is.na(SGP_BASELINE),
# .(CONTENT_AREA, YEAR), GRADE], exclude = NULL)
baseline.names <- grep("BASELINE", names(Colorado_SGP@Data), value = TRUE)
setnames(Colorado_SGP@Data,
baseline.names,
paste0(baseline.names, "_SKIP_YEAR"))
sgps.2019 <- grep(".2019.BASELINE", names(Colorado_SGP@SGP[["SGPercentiles"]]))
names(Colorado_SGP@SGP[["SGPercentiles"]])[sgps.2019] <-
gsub(".2019.BASELINE",
".2019.SKIP_YEAR_BLINE",
names(Colorado_SGP@SGP[["SGPercentiles"]])[sgps.2019])
### Read in SGP Configuration Scripts and Combine
source("SGP_CONFIG/2022/PART_A/ELA.R")
source("SGP_CONFIG/2022/PART_A/MATHEMATICS.R")
CO_Baseline_Config_2019 <- c(
ELA.2019.config,
ELA_PSAT_9.2019.config,
ELA_PSAT_10.2019.config,
ELA_SAT.2019.config,
MATHEMATICS.2019.config,
MATHEMATICS_PSAT_9.2019.config,
MATHEMATICS_PSAT_10.2019.config,
MATHEMATICS_SAT.2019.config
)
### Parallel Config
parallel.config <- list(BACKEND = "PARALLEL",
WORKERS = list(
BASELINE_PERCENTILES = 12,
PROJECTIONS = 6, LAGGED_PROJECTIONS = 4))
### Run abcSGP analysis
Colorado_SGP <-
abcSGP(sgp_object = Colorado_SGP,
years = "2019",
steps = c("prepareSGP", "analyzeSGP", "combineSGP"),
sgp.config = CO_Baseline_Config_2019,
sgp.percentiles = FALSE,
sgp.projections = FALSE,
sgp.projections.lagged = FALSE,
sgp.percentiles.baseline = TRUE,
sgp.projections.baseline = TRUE,
sgp.projections.lagged.baseline = TRUE,
simulate.sgps = FALSE,
parallel.config = parallel.config)
## Changed renaming of results above from '.2019.SKIP_YEAR_BASELINE' to .2019.SKIP_YEAR_BLINE
# table(Colorado_SGP@Data[YEAR == "2019" & is.na(SGP) & !is.na(SGP_BASELINE),
# as.character(SGP_NORM_GROUP_BASELINE)])
# table(Colorado_SGP@Data[YEAR == "2019" & is.na(SGP) & !is.na(SGP_BASELINE),
# SGP_BASELINE == SGP_BASELINE_SKIP_YEAR])
# Colorado_SGP@Data[YEAR == "2019" & is.na(SGP) & !is.na(SGP_BASELINE),
# SGP_BASELINE := NA]
#####
### PART B -- 2022 Cohort and Baseline SGP Analyses
#####
### Load data
load("Data/Colorado_Data_LONG_2022.Rdata")
### Read in SGP Configuration Scripts and Combine
source("SGP_CONFIG/2022/PART_B/ELA.R")
source("SGP_CONFIG/2022/PART_B/MATHEMATICS.R")
CO_Config_2022 <- c(
ELA_2022.config,
ELA_PSAT_9_2022.config,
ELA_PSAT_10_2022.config,
ELA_SAT_2022.config,
MATHEMATICS_2022.config,
MATHEMATICS_PSAT_9_2022.config,
MATHEMATICS_PSAT_10_2022.config,
MATHEMATICS_SAT_2022.config
)
### Parallel Config
parallel.config <- list(BACKEND = "PARALLEL",
WORKERS = list(
PERCENTILES = 12, BASELINE_PERCENTILES = 12,
PROJECTIONS = 6, LAGGED_PROJECTIONS = 4))
### Run updateSGP analysis
Colorado_SGP <-
updateSGP(what_sgp_object = Colorado_SGP,
with_sgp_data_LONG = Colorado_Data_LONG_2022,
years = "2022",
steps = c("prepareSGP", "analyzeSGP", "combineSGP", "outputSGP"),
sgp.config = CO_Config_2022,
sgp.percentiles = TRUE,
sgp.projections = FALSE, # Only Baselines due to checkered priors
sgp.projections.lagged = FALSE,
sgp.percentiles.baseline = TRUE,
sgp.projections.baseline = TRUE,
sgp.projections.lagged.baseline = TRUE,
sgp.target.scale.scores = FALSE, ## Fails due to checkered priors
outputSGP.output.type = c("LONG_Data", "LONG_FINAL_YEAR_Data"),
save.intermediate.results = FALSE,
parallel.config = parallel.config)
### Save results
## Don't save until PSAT/SAT data is available
save(Colorado_SGP, file = "Data/Colorado_SGP.Rdata")