#
# Configurations for different studies
#
# For PISA
pisa_conf <- list(variables = list(pvlabelpref = "PV",
pvlabelsuff = "READ",
weightFinal = "W_FSTUWT",
weightBRR = "W_"),
parameters = list(cutoffs = c(357.77, 420.07, 482.38, 544.68, 606.99, 669.30),
percentiles = c(5, 10, 25, 75, 90, 95),
BRRreps = 80,
weights = "BRR",
replication_scheme = 'pisa')
)
# For LLECE
llece_conf <- list(variables = list(pvlabelpref = "vp",
pvlabelsuff = "READ",
weightFinal = "wgt_sen",
weightBRR = "w_fstr"),
parameters = list(cutoffs = c(676, 729, 813),
percentiles = c(5, 10, 25, 75, 90, 95),
BRRreps = 100,
weights = "BRR",
replication_scheme = 'pisa')
)
# For PIAAC
# http://vs-web-fs-1.oecd.org/piaac/puf-data/SPSS/
piaac_conf <- list(variables = list(pvlabelpref = "PV",
pvlabelsuff = "",
weightFinal = "SPFWT0",
weightBRR = "SPFWT",
countryID = "CNTRYID"),
parameters = list(cutoffs = c(175.99, 225.99, 275.99, 325.99, 375.99),
percentiles = c(5, 10, 25, 75, 90, 95),
PVreps = 10,
BRRreps = 80,
weights = "mixed_piaac",
replication_scheme = 'piaac'),
input = list(type = "OECD",
prefixes = "prg",
type_part = c(-11, -9),
cnt_part = c(-8, -6))
)
# For PASEC
pasec_conf <- list(variables = list(pvlabelpref = "PV",
pvlabelsuff = "LECT",
weight = "rwgt0",
jackknifeZone = "JKZONE",
jackknifeRep = "JKREP"),
parameters = list(cutoffs = c(126, 399.1, 469.5, 540, 610.4),
percentiles = c(5, 10, 25, 75, 90, 95),
weights = "JK",
replication_scheme = 'pasec',
varpv1=FALSE)
)
# For SEA-PLM
sea_conf <- list(variables = list(pvlabelpref = "PV",
pvlabelsuff = "PV",
weight = "WT2019",
weightJK = "rwgt"),
parameters = list(cutoffs = c(274, 289, 304, 317),
percentiles = c(5, 10, 25, 75, 90, 95),
weights = "JK with weights",
replication_scheme = 'sea-plm')
)
# For TIMSS
timss4_conf <- list(variables = list(pvlabelpref="BSMMAT",
pvlabelsuff = "",
weight="TOTWGT",
jackknifeZone = "JKZONE",
jackknifeRep = "JKREP"),
parameters = list(cutoffs = c(400, 475, 550, 625),
percentiles = c(5, 10, 25, 75, 90, 95),
weights = "JK",
PVreps = 5,
varpv1=FALSE),
input = list(type = "IEA",
prefixes = c("asg", "ash", "acg", "ast", "atg"),
student = "asg",
student_colnames1 = c("IDCNTRY", "IDSCHOOL", "IDCLASS", "IDSTUD"),
student_colnames2 = c("JKREP","JKZONE", "HOUWGT", "SENWGT", "TOTWGT"),
student_pattern = "^AS.*0[0-5]$",
home = "ash",
home_colnames = c("IDCNTRY", "IDSTUD"),
school = "acg",
school_colnames = c("IDCNTRY", "IDSCHOOL", "SCHWGT"),
teacher = c("ast","atg"),
teacher_colnames = c("IDCNTRY", "IDTEALIN"),
student_ids = c("IDCNTRY", "IDSTUD"),
school_ids = c("IDCNTRY", "IDSCHOOL"),
type_part = c(-11, -9),
cnt_part = c(-8, -6))
)
timss8_conf <- list(variables = list(pvlabelpref="BSMMAT",
pvlabelsuff = "",
weight="TOTWGT",
jackknifeZone = "JKZONE",
jackknifeRep = "JKREP"),
parameters = list(cutoffs = c(400, 475, 550, 625),
percentiles = c(5, 10, 25, 75, 90, 95),
weights = "JK",
PVreps = 5,
varpv1=FALSE), # change to TRUE for timss < 2015
input = list(type = "IEA",
prefixes = c("bsg", "bcg", "bst", "btm", "bts"),
student = "bsg",
student_colnames1 = c("IDCNTRY", "IDSCHOOL", "IDCLASS", "IDSTUD"),
student_colnames2 = c("JKREP","JKZONE", "HOUWGT", "SENWGT", "TOTWGT"),
student_pattern = "^BS.*0[0-5]$",
school = "bcg",
school_colnames = c("IDCNTRY", "IDSCHOOL", "SCHWGT"),
teacher = c("bst","btm"),
teacher_colnames = c("IDCNTRY", "IDTEALIN"),
student_ids = c("IDCNTRY", "IDSTUD"),
school_ids = c("IDCNTRY", "IDSCHOOL"),
type_part = c(-11, -9),
cnt_part = c(-8, -6))
)
# For PIRLS
pirls_conf <- list(variables = list(pvlabelpref = "ASRREA0",
pvlabelsuff = "",
weight="TOTWGT",
jackknifeZone = "JKZONE",
jackknifeRep = "JKREP"),
parameters = list(cutoffs = c(400, 475, 550, 625),
percentiles = c(5, 10, 25, 75, 90, 95),
weights = "JK",
varpv1=FALSE), # change to TRUE for PIRLS < 2016 (use only 1 PV for sampling error)
input = list(type = "IEA",
prefixes = c("asg", "ash", "ast", "acg", "atg"),
student = "asg",
student_colnames1 = c("IDCNTRY", "IDSCHOOL", "IDCLASS", "IDSTUD"),
student_colnames2 = c("JKREP","JKZONE", "HOUWGT", "SENWGT", "TOTWGT"),
student_pattern = "^ASR.*0[0-5]$",
home = "ash",
home_colnames = c("IDCNTRY", "IDSTUD"),
school = "acg",
school_colnames = c("IDCNTRY", "IDSCHOOL", "SCHWGT"),
teacher = c("ast","atg"),
teacher_colnames = c("IDCNTRY", "IDTEALIN"),
student_ids = c("IDCNTRY", "IDSTUD"),
school_ids = c("IDCNTRY", "IDSCHOOL"),
type_part = c(-11, -9),
cnt_part = c(-8, -6))
)
# ICILS
icils_conf <- list(variables = list(pvlabelpref="BSMMAT",
pvlabelsuff = "",
weight="TOTWGTS",
jackknifeZone = "JKZONES",
jackknifeRep = "JKREPS"),
parameters = list(cutoffs = c(400, 475, 550, 625),
percentiles = c(5, 10, 25, 75, 90, 95),
weights = "JK",
PVreps = 5),
input = list(type = "IEA",
prefixes =c("bsg", "bcg", "btg"),
student = "bsg",
student_colnames1 = c("IDCNTRY", "IDSCHOOL", "IDSTUD"),
student_colnames2 = c("JKREPS","JKZONES", "TOTWGTS"),
student_pattern = "^PV[0-5]CIL$",
school = "bcg",
school_colnames = c("IDCNTRY", "IDSCHOOL", "TOTWGTC"),
teacher = c("btg","btg"),
teacher_colnames = c("IDCNTRY", "IDTEALIN"),
student_ids = c("IDCNTRY", "IDSTUD"),
school_ids = c("IDCNTRY", "IDSCHOOL"),
type_part = c(-11, -9),
cnt_part = c(-8, -6))
)
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