SGP • Student Growth Projections — studentGrowthProjections

studentGrowthProjections(panel.data,
                         sgp.labels,
                         grade.progression,
                         content_area.progression=NULL,
                         year_lags.progression=NULL,
                         grade.projection.sequence=NULL,
                         content_area.projection.sequence=NULL,
                         year_lags.projection.sequence=NULL,
                         max.forward.progression.years=NULL,
                         max.forward.progression.grade=NULL,
                         max.order.for.progression,
                         use.my.knots.boundaries,
                         use.my.coefficient.matrices,
                         panel.data.vnames,
                         achievement.level.prior.vname=NULL,
                         performance.level.cutscores,
                         calculate.sgps=TRUE,
                         convert.0and100=TRUE,
                         trajectories.chunk.size=50000L,
                         sgp.projections.equated=NULL,
                         projection.unit="YEAR",
                         projection.unit.label=NULL,
                         percentile.trajectory.values=NULL,
                         percentile.trajectory.values.max.forward.progression.years=NULL,
                         return.percentile.trajectory.values=NULL,
                         return.projection.group.identifier=NULL,
                         return.projection.group.scale.scores=NULL,
                         return.projection.group.dates=NULL,
                         isotonize=TRUE,
                         lag.increment=0L,
                         lag.increment.label=NULL,
                         sgp.exact.grade.progression=FALSE,
                         projcuts.digits=NULL,
                         sgp.projections.use.only.complete.matrices=NULL,
                         SGPt=NULL,
                         print.time.taken=TRUE)

Arguments

panel.data	Object of class `list` containing longitudinal student data in wide format in `panel.data$Panel_Data`. See `studentGrowthPercentiles` for data requirements. List object must also contain `panel.data$Knots_Boundaries` and `panel.data$Coefficient_Matrices`. See `sgpData` for an exemplar data set. NOTE: The column position of the variables IS IMPORTANT, NOT the names of the variables.
sgp.labels	REQUIRED. A list, `sgp.labels`, of the form `list(my.year= ,` `my.subject= )`. The user-specified values are used to save the percentile growth projections/trajectories and identify coefficient matrices and knots & boundaries for calculation if `use.my.coefficient.matrices` or `use.my.knots.boundaries` is missing. Partly replaces previous argument `proj.function.labels`.
grade.progression	REQUIRED. Argument to specify a student grade/time progression in the data to be used for percentile growth projection/trajectory calculation. This argument helps in replacing previous arguments `num.panels`, `max.num.scores`, and `num.prior.scores`.
content_area.progression	Argument to specify a student content area progression in the data supplied for percentile growth projection/trajectory calculation. Defaults to NULL and is calculated from supplied argument 'sgp.labels'.
year_lags.progression	Argument to specify a student year progression lags in the data supplied for percentile growth projection/trajectory calculation. Defaults to NULL assuming annual increment calculated from supplied argument 'sgp.labels' and 'grade.progression'.
grade.projection.sequence	Argument to manually supply grade sequence over which projection is made. Defaults to NULL and is calculated from available data.
content_area.projection.sequence	Argument to manually supply content area sequence over which projection is made. Defaults to NULL and assumes current year content area is repeated going forward.
year_lags.projection.sequence	Argument to manually supply year lags sequence over which projection is made. Length of supplied sequence should be 1 less than length of supplied 'grade.projection.sequence' and 'content_area.projection.sequence'. Defaults to NULL and assumes annual (1 year lags).
max.forward.progression.years	The MAXIMUM number of years/grades/time periods to project forward conditional upon available coefficient matrices. If missing/NULL (the default), function will project forward as far as allowed by available coefficient matrices.
max.forward.progression.grade	The MAXIMUM grade to project forward based upon available coefficient matrices. If missing/NULL (the default), function will project forward as far as allowed by available coefficient matrices.
max.order.for.progression	Argument to specify the maximum coefficient matrix order to be used for percentile growth projection/trajectory calculation. If missing, the function utilizes the highest matrix order available.
use.my.knots.boundaries	A list of the form `list(my.year= , my.subject= )` specifying the set of pre-calculated knots and boundaries for B-spline calculations. Knot and boundaries are stored (and must be made available) with `panel.data` supplied as a list in `panel.data$Knots_Boundaries$my.year.my.subject`. As of SGP_0.0-6.9 user can also supply a two letter state acronym to utilize knots and boundaries within the `SGPstateData` data set supplied with the SGP package. If missing, function tries to retrieve knots and boundaries from `panel.data$Knots_Boundaries$my.year.my.subject` where `my.year` and `my.subject` are provided by `sgp.labels`.
use.my.coefficient.matrices	A list of the form `list(my.year= , my.subject= )` specifying the set of pre-calculated coefficient matrices to use for percentile growth projection/trajectory calculations. Coefficient matrices are stores (and must be available) with `panel.data` supplied as a list in `panel.data$Coefficient_Matrices` `$my.year.my.subject`. If missing, function tries to retrieve coefficient matrices from `panel.data$Coefficient_Matrices$my.year.my.subject` where `my.year` and `my.subject` are provided by `sgp.labels`.
panel.data.vnames	Vector of variables to use in percentile growth projection/trajectory calculations. If not specified, function attempts to use all available variables.
achievement.level.prior.vname	Character vector indicating variable is supplied panel data corresponding to the prior achievement level to be added to the output. Used in the production of growth to standard analyses.
performance.level.cutscores	Argument for supplying performance level cutscores to be used for determining growth-to-standard percentile growth trajectory calculations. Argument accepts a two letter state acronym (e.g., "CO") that retrieves cutscores that are automatically embedded in a data set contained in the SGP package. Argument also accepts a subject specific list of the form: performance.level.cutscores <- list( Reading=list(GRADE_3=c(cut1, cut2, cut3), GRADE_4=c(cut1, cut2, cut3), . . . GRADE_8=c(cut1, cut2, cut3)), Math=list(GRADE_3=c(cut1, cut2, cut3), . . . GRADE_7=c(cut1, cut2, cut3), GRADE_8=c(cut1, cut2, cut3))) Note that the subject name must match that provided by `sgp.labels`. If cuts are not desired leave the cutscore unspecified, which is the default. If your state's cutscores are not included in the `SGPstateData` data set or are incorrect, please contact dbetebenner@nciea.org to have them added or corrected!
calculate.sgps	Boolean argument (defaults to TRUE) indicating whether to calculate student growth projections. Currently used to bypass calculations in `analyzeSGP` when scale changes occur.
convert.0and100	Boolean argument (defaults to TRUE) indicating whether conversion of growth percentiles of 0 and 100 to growth percentiles of 1 and 99, respectively, occurs. The default produces growth percentiles ranging from 1 to 99.
trajectories.chunk.size	To enhance speed, large data sets are broken up into smaller data sets before trajectories and cuts are calculated. The default chunk.size is 50,000 and is utilized when data sets of over 150 percent of the `trajectory.chunk.size` are passed to `.get.percentile.trajectories` and `.get.trajectories.and.cuts`.
sgp.projections.equated	A list (defaults to NULL) specifying the Year and Linkages associated with the equating used for projection purposes.
projection.unit	Argument specifying the units in which the projections/trajectories and cuts are reported. Either `"GRADE"`, the default, or `"YEAR"`.
projection.unit.label	Argument specifying the label associated with the units in which the projections/trajectories and cuts are reported. Defaults to NULL utilizing the value associated with the argument supplied to `projection.unit`.
percentile.trajectory.values	An integer argument with values ranging from 1 to 100 that returns a vector of percentile trajectory cuts (default is NULL, no percentile trajectory values returned). The returned values are the lower bound for the interval associated with the percentile(s) requested. For example, by specifying 'percentile.trajectory.values=1' the user would receive the conditional .005 quantile associated with each student's distribution. Supplied values can also be a vector of targets that will return Scale Scores associated with those targets.
percentile.trajectory.values.max.forward.progression.years	An integer argument indicating the number of years associated with the trajectory calculated by `percentile.trajectory.values`. Supplied value can also be a vector of targets that will trim the trajectory to fit with a designated number of years.
return.percentile.trajectory.values	A Boolean variable indicating whether to return the percentile trajectory values when they are supplied as targets via panel.data. Default is NULL/FALSE.
return.projection.group.identifier	A Boolean variable indicating whether to return the projection group identifier to distinguish different projection trajectories. Defaults to NULL/FALSE.
return.projection.group.scale.scores	A Boolean variable indicating whether to return the projection group scale scores for each student. Defaults to NULL/FALSE.
return.projection.group.dates	A Boolean variable indicating whether to return the projection group dates associated with the students' scale scores. Defaults to NULL/FALSE.
isotonize	Boolean argument (defaults to TRUE) indicating whether quantile regression results are isotonized to prevent quantile crossing following the methods derived by Chernozhukov, Fernandez-Val and Glichon (2010).
lag.increment	A non-negative integer (defaults to 0) indicating the lag associated with the data supplied for projections. Only relevant if Cutscores or Knots and Boundaries are year dependent.
lag.increment.label	Overrides default ways in which lagged targets and straight targets are labelled ("" and "_CURRENT", respectively).
sgp.exact.grade.progression	A Boolean argument (defaults to FALSE) indicating whether to use the exact grade progression supplied or all orders up to the grade progression supplied.
projcuts.digits	The number of digits (defaults to NULL/0) percentile trajectories (if requested) are formatted.
sgp.projections.use.only.complete.matrices	A Boolean argument (defaults to TRUE) indicating whether projections should be calculated even when all matrices are not available for the given `content_area.projection.sequence` and `grade.projection.sequence`.
SGPt	Character vector indicating the name of the 'DATE' variable to be used for time dependent student growth projection calculations. Defaults to NULL, non-time-dependent SGP calculations.
print.time.taken	Boolean argument (defaults to TRUE) indicating whether to print message indicating information on `studentGrowthProjections` analysis and time taken.

Value

Function returns the input panel.data list object with the additional percentile growth trajectories/percentiles stored in panel.data$SGProjections$my.year.my.subject consisting of student IDs and the associated percentile growth projections/trajectories and cuts. The data frame contains projections/trajectories for each performance level cut-point supplied and each percentile cut the user specifies.

References

Betebenner, D. W. (2008). Toward a normative understanding of student growth. In K. E. Ryan & L. A. Shepard (Eds.), The Future of Test Based Accountability (pp. 155-170). New York: Routledge.

Betebenner, D. W. (2009). Norm- and criterion-referenced student growth. Educational Measurement: Issues and Practice, 28(4):42-51.

Betebenner, D. W. (2012). Growth, standards, and accountability. In G. J. Cizek, Setting Performance Standards: Foundations, Methods & Innovations. 2nd Edition (pp. 439-450). New York: Routledge.

Chernozhukov, V., Fernandez-Val, I. and Galichon, A. (2010), Quantile and Probability Curves Without Crossing. Econometrica, 78: 1093-1125.

Note

Use of this function assumes prior calculation of student growth percentiles, making the coefficient matrices available within the panel.data$Coefficient_Matrices list object. Additionally, if cutscores are desired they must be supplied explicitly by the user (as detailed above in performance.level.cutscores) or included in the SGPstateData data set. If your state's cutscores are not included or are incorrect, please contact dbetebenner@nciea.org to have cutscores added or corrected!

Examples

not_run({
  ## First calculate SGPs for 2014
  my.grade.sequences <- list(3:4, 3:5, 3:6, 3:7, 4:8)
  my.sgpData <- list(Panel_Data = sgpData)

  for (i in seq_along(my.grade.sequences)) {
        my.sgpData <- studentGrowthPercentiles(panel.data=my.sgpData,
                sgp.labels=list(my.year=2014, my.subject="Reading"),
                use.my.knots.boundaries="DEMO",
                grade.progression=my.grade.sequences[[i]])
  }

  ## Calculate Growth Projections

  my.grade.progressions <- list(3, 3:4, 3:5, 3:6, 4:7)

  for (i in seq_along(my.grade.progressions)) {
        my.sgpData <- studentGrowthProjections(panel.data=my.sgpData,
                sgp.labels=list(my.year=2014, my.subject="Reading"),
                projcuts.digits=0,
                projection.unit="GRADE",
                performance.level.cutscores="DEMO",
                percentile.trajectory.values=c(25, 50, 75),
                grade.progression=my.grade.progressions[[i]])
  }

  ##  Save the Student Growth Projections Results to a .csv file:

  write.csv(my.sgpData$SGProjections$READING.2014,
  file= "2014_Reading_SGProjections.csv", row.names=FALSE, quote=FALSE)
})

Student Growth Projections

Arguments

Value

References

Note

See also

Examples

Contents

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