Rach: _Content Mastery_ Subject-Area Indicators' Points (in...

In EccRiley/ccrpi: Calculate Georgia (U.S.) Schools' College & Career Ready Performanc Index (CCRPI) Scores in R

Description

Compute subject-area indicator points for the Content Mastery CCRPI component, overall (per individual school, or across multiple schools within the same gradeband) or by subgroup(s).

Usage

Rach(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"),
  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, ...)

Arguments

x	A dataframe or object coercible to a dataframe containing student-level GA Milestones data containing all necessary columns (see additional arguments below) for computing school-level Content Mastery points for a single subject-area indicator.
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).
grade_var	A character vector of length 1 specifying the column name in x containing students' grade level
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.
subject_var	A character vector of length 1 specifying the column name in x containing the appropriate subject area codes.
subject_code	A character vector specifying the actual codes used in x$subject_var for the subject area specified in subject.
assessment_type_var	A character vector of length 1 specifying the column name in x containing the assessment types (e.g., "EOG", "EOC", "GAA", etc.).
assessment_type_codes	A character vector specifying the acceptable values of assessment_type_var for use in computing content mastery scores.
fay_var	A character vector of length 1 specifying the column name in x containing the FAY Participant filter.
fay_code	A character vector specifying acceptable values of fay_var for the FAY filter.
performance_code_var	A character vector of length 1 specifying the column name in x containing the assessment performance codes (e.g., "BEG", "DEV", "PRO", "DIS").
valid_performance_codes	A character vector specifying the acceptable performance code values under performance_code_var.
group_var	An optional character vector specifying the column name in x containing the appropriate variable for the focal subgroup (see Details and Rcgpts).
group	A character vector specifying the appropriate subgroup under group_var (ignored if group_var is NULL).
return_new_x	logical. If 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 Content Mastery points dataframe.
rec.cmlvls	A character vector of (pseudo) length 1 providing the 'recodes' string to be passed to car::recode() for the re-labeling Content Mastery achievement levels.
rec.cmpnts	A character vector of (pseudo) length 1 providing the 'recodes' string to be passed to car::recode() for assigning point values corresponding to the Content Mastery achievement levels.

Value

A list containing the following components:

1. 'new_x': The final ‘dataframe' used in computing the subject-area’s Content Mastery scores (see details).

2. 'cm.subj': A dataframe containing the computed 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.

Details

'new_x', if returned, contains all columns in the original input dataframe ('x'), along with two new columns: "osa.performance.lvl" and "ccrpi.points". The former is a relabeled version of x[["osa.performance.code"]], while "ccrpi.points" contains the point-value assignment corresponding to each students' achievement level (per recode values specified in 'rec.cmpts').

The table below provides details for the contents of 'cm.subj' (i.e., the returned dataframe containing the computed points for the focal Content Mastery subject-area indicator):

[,1]	school.id	integer	School ID number from 'x'
[,2]	N_Students.SUBJ	integer	Number of students with valid test scores
[,3]	SumPts.SUBJ	double	Count of achievement points earned across test takers
[,4]	AchPts.SUBJ	double	Subject-area achievement points (see details and 'new_x[["ccrpi.points"]]' description above)
[,5]	AchPts_Cpd.SUBJ	double	AchPts.SUBJ, capped at 1.000 point (analygous 100%)
[,6]	AchPts_Wgtd.SUBJ	double	AchPts_Cpd.SUBJ weighted according to gradeband-specific weighting rules for the focal subject-area indicator

Note that ".SUBJ" in the column labels above is a generic placeholder for the actual subject-area label (per user-specified value for 'subject_lab') (e.g., if subject_lab == "ELA", then 'SumPts.SUBJ' above would actually be 'SumPts.ELA' in the returned 'cm.subj' dataframe.

EccRiley/ccrpi documentation built on May 17, 2019, 7:47 a.m.