R/Rach.R
In EccRiley/ccrpi: Calculate Georgia (U.S.) Schools' College & Career Ready Performanc Index (CCRPI) Scores in R
Defines functions
Rach
Documented in
Rach
#' \emph{Content Mastery} Subject-Area Indicators' Points (\code{DRAFT RD})
#'
#' Compute subject-area indicator points for the \emph{Content Mastery CCRPI} component, overall (per individual school, or across multiple schools within the same gradeband) or by subgroup(s).
#'
#' @param x A \code{dataframe} or object coercible to a \code{dataframe} containing \emph{\strong{student-level} GA Milestones} data containing all necessary columns (see additional arguments below) for computing \emph{\strong{school-level} Content Mastery} points for a single subject-area indicator.
#' @param gradeband A character vector of length 1 specifying the focal gradeband as one of the following: "ES" for elementary schools (grades 3 - 5), "MS" for middle schools (grades 6 - 8), or "HS" (grades 9 - 12).
#' @param grade_var A character vector of length 1 specifying the column name in \code{x} containing students' grade level
#' @param subject A character vector of length 1 specifying the focal subject area s one of the following: "ELA" for English/Language Arts, "MATH" for Mathematics, "SCI" for Science, or "SS" for Social Studies.
#' @param subject_var A character vector of length 1 specifying the column name in \code{x} containing the appropriate subject area codes.
#' @param subject_code A character vector specifying the actual codes used in \code{x$subject_var} for the subject area specified in \code{subject}.
#' @param assessment_type_var A character vector of length 1 specifying the column name in \code{x} containing the assessment types (e.g., "EOG", "EOC", "GAA", etc.).
#' @param assessment_type_codes A character vector specifying the acceptable values of \code{assessment_type_var} for use in computing content mastery scores.
#' @param fay_var A character vector of length 1 specifying the column name in \code{x} containing the \emph{FAY Participant} filter.
#' @param fay_code A character vector specifying acceptable values of \code{fay_var} for the \emph{FAY} filter.
#' @param performance_code_var A character vector of length 1 specifying the column name in \code{x} containing the assessment performance codes (e.g., "BEG", "DEV", "PRO", "DIS").
#' @param valid_performance_codes A character vector specifying the acceptable performance code values under \code{performance_code_var}.
#' @param keynames A character vector of length 3 providing the variable names in \code{x} corresponding to: \code{c("school.id", "school.year", "gtid")}.
#' @param rec_cmlvls A character vector of (pseudo) length 1 providing the \code{'recodes'} string to be passed to \code{\link[car]{car::recode()}} for the re-labeling \emph{Content Mastery} achievement levels.
#' @param rec_cmpnts A character vector of (pseudo) length 1 providing the \code{'recodes'} string to be passed to \code{\link[car]{car::recode()}} for assigning point values corresponding to the \emph{Content Mastery} achievement levels.
#' @param group_var An \emph{optional} character vector specifying the column name in \code{x} containing the appropriate variable for the focal subgroup (see \emph{Details} and \code{\link{Rcgpts}}).
#' @param group A character vector specifying the appropriate subgroup under \code{group_var} (ignored if \code{group_var} is \code{NULL}).
#' @param return_new_x logical. If \code{TRUE} (the default), the final returned value is a list containing (1) the manipulated version of the input dataframe (`x`), for QC purposes, and (2) the computed subject-level \emph{Content Mastery} points dataframe.
#'
#' @return A list containing the following components:
#'
#' \enumerate{
#' \item \code{\strong{'new_x'}}: The final `dataframe` used in computing the subject-area's \emph{Content Mastery} scores (see details).
#' \item \code{\strong{'cm.subj'}}: A dataframe containing the computed \emph{Content Mastery} score(s) for the user-specified subject-area and gradeband. The table below provides additional details on the columns returned in this dataframe (see details.
#' }
#'
#' @section Details:
#'
#' \strong{\code{'new_x'}}, if returned, contains all columns in the original input \code{dataframe} (\strong{\code{'x'}}), along with two new columns: \code{\emph{"osa.performance.lvl"}} and \code{\emph{"ccrpi.points"}}.
#' The former is a relabeled version of \code{x[["osa.performance.code"]]}, while \code{\emph{"ccrpi.points"}} contains the point-value assignment corresponding to each students' achievement level (per recode values specified in '\code{rec_cmpts}').
#'
#' The table below provides details for the contents of \strong{\code{'cm.subj'}} (i.e., the returned dataframe containing the computed points for the focal \emph{Content Mastery} subject-area indicator):
#'
#' \tabular{rlll}{
#' [,1] \tab \code{\emph{school.id}} \tab integer \tab School ID number from \code{\strong{'x'}} \cr
#' [,2] \tab \code{\emph{N_Students.SUBJ}} \tab integer \tab Number of students with valid test scores \cr
#' [,3] \tab \code{\emph{SumPts.SUBJ}} \tab double \tab Count of achievement points earned across test takers \cr
#' [,4] \tab \code{\emph{AchPts.SUBJ}} \tab double \tab Subject-area \emph{achievement points} (see details and \code{'new_x[["ccrpi.points"]]'} description above) \cr
#' [,5] \tab \code{\emph{AchPts_Cpd.SUBJ}} \tab double \tab \code{\emph{AchPts.SUBJ}}, capped at 1.000 point (analygous 100\%) \cr
#' [,6] \tab \code{\emph{AchPts_Wgtd.SUBJ}} \tab double \tab \code{\emph{AchPts_Cpd.SUBJ}} weighted according to gradeband-specific weighting rules for the focal subject-area indicator \cr
#' }
#'
#' Note that \code{".SUBJ"} in the column labels above is a generic placeholder for the actual subject-area label (per user-specified value for \code{'subject_lab'}) (e.g., if \code{subject_lab == "ELA"}, then \code{\emph{'SumPts.SUBJ'}} above would actually be \code{\emph{'SumPts.ELA'}} in the returned \code{\strong{'cm.subj'}} dataframe.
#'
#'
#' @export
Rach <- function(x, gradeband, grade_var = "student.grade.level",
subject, subject_var, subject_code,
assessment_type_var,
assessment_type_codes = c("EOG", "EOC", "GAA"),
fay_var, fay_code = "Y",
performance_code_var = "osa.performance.code",
valid_performance_codes = c("BEG", "DNM", "DEV", "PRO", "ADV", "DIS"),
keynames = c("school.id", "school.year", "gtid"),
rec_cmlvls = c("'BEG' = 'L1'; 'DNM' = 'L1'; 'DEV' = 'L2'; 'PRO' = 'L3'; 'ADV' = 'L3'; 'DIS' = 'L4'"),
rec_cmpnts = c("'BEG' = 0; 'DNM' = 0; 'DEV' = 0.5; 'PRO' = 1; 'ADV' = 1; 'DIS' = 1.5"),
group_var = NULL, group = NULL, return_new_x = TRUE, ...) {
## PREEMPTIVELY ENSURE 'X' IS A DATA.FRAME CLASS OBJECT TO START OUT (NOT A DATA.TABLE OBJECT YET) ##
x <- as.data.frame(x)
## 'newxvars': LIST OF ALL ESSENTIAL VARS (INCL. SUBGROUPS' VARS) FOR CONTENT MASTERY OUTPUT DF ##
newxvars <- c(keynames, "school.name", "N_Students",
"fay.participant", grade_var, "gender.code", "race.code", "el", "ed", "swd", "all",
assessment_type_var, performance_code_var, "osa.performance.lvl",
"SumPts", "AchPts", "AchPts_Cpd", "AchPts_Wgtd", "ccrpi.points")
## NOTE: ['SumPts', 'AchPts', 'AchPts_Cpd', 'AchPts_Wgtd', & 'CCRPI_POINTS'] ARE CREATED BELOW ##
### RESTRICT X TO SPECIFIED GROUP (IF APPLICABLE) ####
if (!is.null(group_var)) {
x <- x[x[[group_var]] == group, , drop = FALSE]
}
### RESTRICT TO VALID ASSESSMENT TYPES ('assessment_type_var'): ####
x <- x[x[[assessment_type_var]] %in% assessment_type_codes, ]
### RESTRICT TO APPROPRIATE GRADE LEVELS BASED ON USER-SPECIFIED GRADEBAND ####
if (gradeband == "MS") {
## HIGH SCHOOLS ##
x <- x[x[[grade_var]] %in% c(6, 7, 8), , drop = FALSE]
} else if (gradeband == "HS") {
## MIDDLE SCHOOLS ##
x <- x[x[[grade_var]] >= 9, , drop = FALSE]
} else if (gradeband == "ES") {
## ELEMENTARY SCHOOLS ##
x <- x[x[[grade_var]] <= 5, , drop = FALSE]
} else stop("Unusable Grade Band")
### RESTRICT TO VALID ACHIEVEMENT LEVEL CODES ####
x <- x[x[[performance_code_var]] %in% valid_performance_codes, , drop = FALSE]
### FILTER ON FAY & FOCAL SUBJECT AREA ####
## (... & CREATE 'new_x' AS A DATA.TABLE-CLASSED COPY OF 'x', RETAINING ONLY VARIABLES CM-RELEVANT) ##
library(data.table)
new_x <- x[x[[fay_var]] == fay_code & x[[subject_var]] %in% subject_code,
names(x) %in% newxvars, drop = FALSE]
setDT(new_x, key = keynames[[1]])
### RECODE OSA.PERFORMANCE.CODE ####
## (... TO ENSURE THAT THE ACH-PT LEVELS ARE ORDERED CORRECTLY IN TABULATED OUTPUTS LATER) ##
new_x[, performance.lvl := car::recode(new_x[[performance_code_var]], rec_cmlvls)] ## SEE 'rec_cmlvls' ARG DESC ##
### CREATE NEW "ccrpi.points" COLUMN (PER D.JAFFE) <==> EACH STUDENT'S ACH. PTS. EARNED ON THE INPUT SUBJ. ##
new_x[, ccrpi.points := car::recode(new_x[[performance_code_var]], rec_cmpnts)] ## SEE 'rec_cmpnts' ARG DESC ##
cm.subj <- new_x[, .(N_Students = .N, ## COMPUTE NUMBER OF VALID TEST RESULTS FOR THE FOCAL SUBJ. ##
SumPts = sum(ccrpi.points), ## COMPUTE TOTAL ACH.PTS. EARNED ON THE FOCAL SUBJ. ##
AchPts = sum(ccrpi.points)/.N), ## COMPUTE SUBJ. INDICATOR'S CCRPI PTS ##
by = c(key(new_x))] ## DO ALL OF THE ABOVE BY SCHOOL ##
### ... (NOTE: SUBJ. INDICATOR CCRPI PTS ARE COMPUTED AS A FUNCTION OF [TOTAL ACH.PTS. EARNED] DIVIDED BY [NUMBER OF VALID TEST RESULTS] FOR THE FOCAL SUBJ. - THE RESULTING SCHOOL-LEVEL INDICATOR SCORE IS ROUNDED TO 2 DECIMAL PLACES, PER 2018 CALCULATION GUIDE) ###
## CAP SUBJ. INDICATOR ACHIEVEMENT POINTS AT 100% (i.e., 1.0pts) ##
cm.subj[, AchPts_Cpd := ifelse(AchPts >= 1.0000, 1, AchPts)]
## IMPLEMENT GRADEBAND-SPECIFIC RULES FOR CONTENT MASTERY COMPONENT SCORE WEIGHTS: ##
if (gradeband == 'HS') {
cmwgt <- 0.25
} else if (gradeband %in% c("MS", "ES")) {
if (subject %in% c("ELA", "MATH")) {
cmwgt <- 0.375
} else if (subject %in% c("SCI", "SS")) {
cmwgt <- 0.125
}
}
### APPLY CONTENT MASTERY WEIGHT (BASED ON GRADEBAND) TO CAPPED SUBJ. INDICATOR SCORES ####
cm.subj[, AchPts_Wgtd := AchPts_Cpd*cmwgt]
## APPEND SUBJ. LABEL TO COMPUTED VARIABLES' COLNAMES ##
names(cm.subj)[-1] <- paste0(names(cm.subj)[-1], ".", subject)
setnames(new_x, "ccrpi.points", paste0("ccrpi.points.", subject))
### RETURN OUTPUT(S) ####
## BY DEFAULT, 'new_x' DF IS RETURNED ALONG WITH CM.SUBJ. DF ##
res.all <- list(new_x = new_x, cm.subj = cm.subj)
if (return_new_x == TRUE) {
return(res.all)
} else return(cm.subj)
}
#'
#' @section Examples (todo):
#'
EccRiley/ccrpi documentation built on May 17, 2019, 7:47 a.m.
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Defines functions Rach
Documented in Rach
#' \emph{Content Mastery} Subject-Area Indicators' Points (\code{DRAFT RD})
#'
#' Compute subject-area indicator points for the \emph{Content Mastery CCRPI} component, overall (per individual school, or across multiple schools within the same gradeband) or by subgroup(s).
#'
#' @param x A \code{dataframe} or object coercible to a \code{dataframe} containing \emph{\strong{student-level} GA Milestones} data containing all necessary columns (see additional arguments below) for computing \emph{\strong{school-level} Content Mastery} points for a single subject-area indicator.
#' @param gradeband A character vector of length 1 specifying the focal gradeband as one of the following: "ES" for elementary schools (grades 3 - 5), "MS" for middle schools (grades 6 - 8), or "HS" (grades 9 - 12).
#' @param grade_var A character vector of length 1 specifying the column name in \code{x} containing students' grade level
#' @param subject A character vector of length 1 specifying the focal subject area s one of the following: "ELA" for English/Language Arts, "MATH" for Mathematics, "SCI" for Science, or "SS" for Social Studies.
#' @param subject_var A character vector of length 1 specifying the column name in \code{x} containing the appropriate subject area codes.
#' @param subject_code A character vector specifying the actual codes used in \code{x$subject_var} for the subject area specified in \code{subject}.
#' @param assessment_type_var A character vector of length 1 specifying the column name in \code{x} containing the assessment types (e.g., "EOG", "EOC", "GAA", etc.).
#' @param assessment_type_codes A character vector specifying the acceptable values of \code{assessment_type_var} for use in computing content mastery scores.
#' @param fay_var A character vector of length 1 specifying the column name in \code{x} containing the \emph{FAY Participant} filter.
#' @param fay_code A character vector specifying acceptable values of \code{fay_var} for the \emph{FAY} filter.
#' @param performance_code_var A character vector of length 1 specifying the column name in \code{x} containing the assessment performance codes (e.g., "BEG", "DEV", "PRO", "DIS").
#' @param valid_performance_codes A character vector specifying the acceptable performance code values under \code{performance_code_var}.
#' @param keynames A character vector of length 3 providing the variable names in \code{x} corresponding to: \code{c("school.id", "school.year", "gtid")}.
#' @param rec_cmlvls A character vector of (pseudo) length 1 providing the \code{'recodes'} string to be passed to \code{\link[car]{car::recode()}} for the re-labeling \emph{Content Mastery} achievement levels.
#' @param rec_cmpnts A character vector of (pseudo) length 1 providing the \code{'recodes'} string to be passed to \code{\link[car]{car::recode()}} for assigning point values corresponding to the \emph{Content Mastery} achievement levels.
#' @param group_var An \emph{optional} character vector specifying the column name in \code{x} containing the appropriate variable for the focal subgroup (see \emph{Details} and \code{\link{Rcgpts}}).
#' @param group A character vector specifying the appropriate subgroup under \code{group_var} (ignored if \code{group_var} is \code{NULL}).
#' @param return_new_x logical. If \code{TRUE} (the default), the final returned value is a list containing (1) the manipulated version of the input dataframe (`x`), for QC purposes, and (2) the computed subject-level \emph{Content Mastery} points dataframe.
#'
#' @return A list containing the following components:
#'
#' \enumerate{
#' \item \code{\strong{'new_x'}}: The final `dataframe` used in computing the subject-area's \emph{Content Mastery} scores (see details).
#' \item \code{\strong{'cm.subj'}}: A dataframe containing the computed \emph{Content Mastery} score(s) for the user-specified subject-area and gradeband. The table below provides additional details on the columns returned in this dataframe (see details.
#' }
#'
#' @section Details:
#'
#' \strong{\code{'new_x'}}, if returned, contains all columns in the original input \code{dataframe} (\strong{\code{'x'}}), along with two new columns: \code{\emph{"osa.performance.lvl"}} and \code{\emph{"ccrpi.points"}}.
#' The former is a relabeled version of \code{x[["osa.performance.code"]]}, while \code{\emph{"ccrpi.points"}} contains the point-value assignment corresponding to each students' achievement level (per recode values specified in '\code{rec_cmpts}').
#'
#' The table below provides details for the contents of \strong{\code{'cm.subj'}} (i.e., the returned dataframe containing the computed points for the focal \emph{Content Mastery} subject-area indicator):
#'
#' \tabular{rlll}{
#' [,1] \tab \code{\emph{school.id}} \tab integer \tab School ID number from \code{\strong{'x'}} \cr
#' [,2] \tab \code{\emph{N_Students.SUBJ}} \tab integer \tab Number of students with valid test scores \cr
#' [,3] \tab \code{\emph{SumPts.SUBJ}} \tab double \tab Count of achievement points earned across test takers \cr
#' [,4] \tab \code{\emph{AchPts.SUBJ}} \tab double \tab Subject-area \emph{achievement points} (see details and \code{'new_x[["ccrpi.points"]]'} description above) \cr
#' [,5] \tab \code{\emph{AchPts_Cpd.SUBJ}} \tab double \tab \code{\emph{AchPts.SUBJ}}, capped at 1.000 point (analygous 100\%) \cr
#' [,6] \tab \code{\emph{AchPts_Wgtd.SUBJ}} \tab double \tab \code{\emph{AchPts_Cpd.SUBJ}} weighted according to gradeband-specific weighting rules for the focal subject-area indicator \cr
#' }
#'
#' Note that \code{".SUBJ"} in the column labels above is a generic placeholder for the actual subject-area label (per user-specified value for \code{'subject_lab'}) (e.g., if \code{subject_lab == "ELA"}, then \code{\emph{'SumPts.SUBJ'}} above would actually be \code{\emph{'SumPts.ELA'}} in the returned \code{\strong{'cm.subj'}} dataframe.
#'
#'
#' @export
Rach <- function(x, gradeband, grade_var = "student.grade.level",
subject, subject_var, subject_code,
assessment_type_var,
assessment_type_codes = c("EOG", "EOC", "GAA"),
fay_var, fay_code = "Y",
performance_code_var = "osa.performance.code",
valid_performance_codes = c("BEG", "DNM", "DEV", "PRO", "ADV", "DIS"),
keynames = c("school.id", "school.year", "gtid"),
rec_cmlvls = c("'BEG' = 'L1'; 'DNM' = 'L1'; 'DEV' = 'L2'; 'PRO' = 'L3'; 'ADV' = 'L3'; 'DIS' = 'L4'"),
rec_cmpnts = c("'BEG' = 0; 'DNM' = 0; 'DEV' = 0.5; 'PRO' = 1; 'ADV' = 1; 'DIS' = 1.5"),
group_var = NULL, group = NULL, return_new_x = TRUE, ...) {
## PREEMPTIVELY ENSURE 'X' IS A DATA.FRAME CLASS OBJECT TO START OUT (NOT A DATA.TABLE OBJECT YET) ##
x <- as.data.frame(x)
## 'newxvars': LIST OF ALL ESSENTIAL VARS (INCL. SUBGROUPS' VARS) FOR CONTENT MASTERY OUTPUT DF ##
newxvars <- c(keynames, "school.name", "N_Students",
"fay.participant", grade_var, "gender.code", "race.code", "el", "ed", "swd", "all",
assessment_type_var, performance_code_var, "osa.performance.lvl",
"SumPts", "AchPts", "AchPts_Cpd", "AchPts_Wgtd", "ccrpi.points")
## NOTE: ['SumPts', 'AchPts', 'AchPts_Cpd', 'AchPts_Wgtd', & 'CCRPI_POINTS'] ARE CREATED BELOW ##
### RESTRICT X TO SPECIFIED GROUP (IF APPLICABLE) ####
if (!is.null(group_var)) {
x <- x[x[[group_var]] == group, , drop = FALSE]
}
### RESTRICT TO VALID ASSESSMENT TYPES ('assessment_type_var'): ####
x <- x[x[[assessment_type_var]] %in% assessment_type_codes, ]
### RESTRICT TO APPROPRIATE GRADE LEVELS BASED ON USER-SPECIFIED GRADEBAND ####
if (gradeband == "MS") {
## HIGH SCHOOLS ##
x <- x[x[[grade_var]] %in% c(6, 7, 8), , drop = FALSE]
} else if (gradeband == "HS") {
## MIDDLE SCHOOLS ##
x <- x[x[[grade_var]] >= 9, , drop = FALSE]
} else if (gradeband == "ES") {
## ELEMENTARY SCHOOLS ##
x <- x[x[[grade_var]] <= 5, , drop = FALSE]
} else stop("Unusable Grade Band")
### RESTRICT TO VALID ACHIEVEMENT LEVEL CODES ####
x <- x[x[[performance_code_var]] %in% valid_performance_codes, , drop = FALSE]
### FILTER ON FAY & FOCAL SUBJECT AREA ####
## (... & CREATE 'new_x' AS A DATA.TABLE-CLASSED COPY OF 'x', RETAINING ONLY VARIABLES CM-RELEVANT) ##
library(data.table)
new_x <- x[x[[fay_var]] == fay_code & x[[subject_var]] %in% subject_code,
names(x) %in% newxvars, drop = FALSE]
setDT(new_x, key = keynames[[1]])
### RECODE OSA.PERFORMANCE.CODE ####
## (... TO ENSURE THAT THE ACH-PT LEVELS ARE ORDERED CORRECTLY IN TABULATED OUTPUTS LATER) ##
new_x[, performance.lvl := car::recode(new_x[[performance_code_var]], rec_cmlvls)] ## SEE 'rec_cmlvls' ARG DESC ##
### CREATE NEW "ccrpi.points" COLUMN (PER D.JAFFE) <==> EACH STUDENT'S ACH. PTS. EARNED ON THE INPUT SUBJ. ##
new_x[, ccrpi.points := car::recode(new_x[[performance_code_var]], rec_cmpnts)] ## SEE 'rec_cmpnts' ARG DESC ##
cm.subj <- new_x[, .(N_Students = .N, ## COMPUTE NUMBER OF VALID TEST RESULTS FOR THE FOCAL SUBJ. ##
SumPts = sum(ccrpi.points), ## COMPUTE TOTAL ACH.PTS. EARNED ON THE FOCAL SUBJ. ##
AchPts = sum(ccrpi.points)/.N), ## COMPUTE SUBJ. INDICATOR'S CCRPI PTS ##
by = c(key(new_x))] ## DO ALL OF THE ABOVE BY SCHOOL ##
### ... (NOTE: SUBJ. INDICATOR CCRPI PTS ARE COMPUTED AS A FUNCTION OF [TOTAL ACH.PTS. EARNED] DIVIDED BY [NUMBER OF VALID TEST RESULTS] FOR THE FOCAL SUBJ. - THE RESULTING SCHOOL-LEVEL INDICATOR SCORE IS ROUNDED TO 2 DECIMAL PLACES, PER 2018 CALCULATION GUIDE) ###
## CAP SUBJ. INDICATOR ACHIEVEMENT POINTS AT 100% (i.e., 1.0pts) ##
cm.subj[, AchPts_Cpd := ifelse(AchPts >= 1.0000, 1, AchPts)]
## IMPLEMENT GRADEBAND-SPECIFIC RULES FOR CONTENT MASTERY COMPONENT SCORE WEIGHTS: ##
if (gradeband == 'HS') {
cmwgt <- 0.25
} else if (gradeband %in% c("MS", "ES")) {
if (subject %in% c("ELA", "MATH")) {
cmwgt <- 0.375
} else if (subject %in% c("SCI", "SS")) {
cmwgt <- 0.125
}
}
### APPLY CONTENT MASTERY WEIGHT (BASED ON GRADEBAND) TO CAPPED SUBJ. INDICATOR SCORES ####
cm.subj[, AchPts_Wgtd := AchPts_Cpd*cmwgt]
## APPEND SUBJ. LABEL TO COMPUTED VARIABLES' COLNAMES ##
names(cm.subj)[-1] <- paste0(names(cm.subj)[-1], ".", subject)
setnames(new_x, "ccrpi.points", paste0("ccrpi.points.", subject))
### RETURN OUTPUT(S) ####
## BY DEFAULT, 'new_x' DF IS RETURNED ALONG WITH CM.SUBJ. DF ##
res.all <- list(new_x = new_x, cm.subj = cm.subj)
if (return_new_x == TRUE) {
return(res.all)
} else return(cm.subj)
}
#'
#' @section Examples (todo):
#'
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