SGP (version 0.0-8.0)

abcSGP: Perform 4 step sequence: prepareSGP, analyzeSGP, combineSGP, and summarizeSGP

Description

Utility function to perform sequence of steps going from data preparation, prepareSGP, SGP data analysis, analyzeSGP, data combining, combineSGP, and data summarization, summarizeSGP. Calculating and using student growth percentiles is as easy as ABC.

Usage

abcSGP(sgp_object,
    state,
    steps=c("prepareSGP", "analyzeSGP", "combineSGP", "summarizeSGP", "reportSGP"),
    years,
    content_areas,
    grades,
    sgp.percentiles=TRUE,
    sgp.projections=TRUE,
    sgp.projections.lagged=TRUE,
    simulate.sgps=TRUE,
    save.intermediate.results=FALSE,
    sgp.summaries=list(MEDIAN_SGP="median_na(SGP)",
       MEDIAN_SGP_TARGET="median_na(SGP_TARGET)",
       PERCENT_CATCHING_UP_KEEPING_UP="percent_in_category(CATCH_UP_KEEP_UP_STATUS, list(c('Catch Up: Yes', 'Keep Up: Yes')), list(c('Catch Up: Yes', 'Catch Up: No', 'Keep Up: Yes', 'Keep Up: No')))",
       MEDIAN_SGP_COUNT="num_non_missing(SGP)",
       PERCENT_AT_ABOVE_PROFICIENT=
           "percent_in_category(ACHIEVEMENT_LEVEL, list(c('Proficient', 'Advanced')), list(c('Unsatisfactory', 'Partially Proficient', 'Proficient', 'Advanced')))",
       PERCENT_AT_ABOVE_PROFICIENT_COUNT=
           "num_non_missing(ACHIEVEMENT_LEVEL)"),
    summary.groups=list(institution=c("STATE", "DISTRICT_NUMBER", "SCHOOL_NUMBER"),
       content="CONTENT_AREA",
       time="YEAR",
       institution_level="GRADE",
       demographic=c("GENDER", "ETHNICITY", "FREE_REDUCED_LUNCH_STATUS",
           "ELL_STATUS", "IEP_STATUS", "GIFTED_AND_TALENTED_PROGRAM_STATUS", "CATCH_UP_KEEP_UP_STATUS_INITIAL"),
       institution_inclusion=list(STATE="STATE_ENROLLMENT_STATUS",
            DISTRICT_NUMBER="DISTRICT_ENROLLMENT_STATUS", 
            SCHOOL_NUMBER="SCHOOL_ENROLLMENT_STATUS")),
    confidence.interval.groups=list(institution="SCHOOL_NUMBER",
       content="CONTENT_AREA",
       time="YEAR",
       institution_level= NULL,
       demographic=NULL,
       institution_inclusion=list(STATE=NULL,
            DISTRICT_NUMBER=NULL, 
            SCHOOL_NUMBER="SCHOOL_ENROLLMENT_STATUS")))

Arguments

sgp_object
A list containing LONG formatted data. See sgpData_LONG for an exemplar.
state
Acronym indicating state associated with the data for access to embedded knot and boundaries, cutscores, CSEMs, and other relevant state level data.
steps
Vector containing all or some subset of prepareSGP, analyzeSGP, combineSGP,
years
A vector indicating year(s) in which to produce student growth percentiles and/or student growth projections/trajectories. If missing the function will use the data to infer the year(s) in which to perform growth percentile analyses based upon the assum
content_areas
A vector indicating content area(s) in which to produce student growth percentiles and/or student growth projections/trajectories. If missing the function will use the data to infer the content area(s) available for analyses.
grades
A vector indicating grades for which to calculate student growth percentiles and/or student growth projections/trajectories. If missing the function will use the data to infer all the grade progressions for student growth percentile and student growth pr
sgp.percentiles
Boolean variable indicating whether to calculate student growth percentiles. Defaults to TRUE.
sgp.projections
Boolean variable indicating whether to calculate student growth projections. Defaults to TRUE.
sgp.projections.lagged
Boolean variable indicating whether to calculate lagged student growth projections often used for growth to standard analyses. Defaults to TRUE.
simulate.sgps
Boolean variable indicating whether to simulate SGP values for students based on test-specific Conditional Standard Errors of Measurement (CSEM). Test CSEM data must be available for simulation. Must be set to TRUE for confidence interval construction.
save.intermediate.results
Should intermediate results of abcSGP be saved after each of prepareSGP, analyzeSGP, combineSGP
sgp.summaries
A list giving the summaries requested for each group analyzed based upon the summary.group argument.
summary.groups
A list consisting of 5 types of groups across which all summaries are taken: institution, content, time, institution_level, demographic, and institution_inclusion. Summaries gen
confidence.interval.groups
A subset of the groups provided in the summary.groups argument indicating which groups to provide confidence intervals for. See documentation for summarizeSGP and

Value

  • Function returns a list containing the input long data set in the Student slot as a data.table keyed using VALID_CASE, CONTENT_AREA, YEAR, ID, SGP results including student growth percentile and student growth projections/trajectories in the SGP slot, and summary results in the Summary slot.

See Also

sgpData_LONG, prepareSGP, analyzeSGP, combineSGP, summarizeSGP, studentGrowthPercentiles, and studentGrowthProjections

Examples

Run this code
DEMO_Data <- abcSGP(sgp_object=sgpData_LONG, state="DEMO")

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