Description Usage Arguments Details Value
project_s2s
accepts a single season, which
must be "Spring", cdf and creates a second season with projected
growth, and appends the projected growth to the original cdf.
1 2 3 4 5 | project_s2s(.data, student_column = "studentid", grade_column = "grade",
subject_column = "measurementscale", rit_column = "testritscore",
term_column = "termname", dl_indicator = "iep", ell_indicator = "iep",
school_indicator = "schoolname", fall_equate_scores = NULL,
percent_cr = 0.1)
|
.data |
a long format (i.e., combined) Comprehensive Data File |
student_column |
column that uniquely identifies students with respect to subject and term |
grade_column |
column that identifies grade levels |
subject_column |
which column identifies measurement scale |
rit_column |
column that identifes RIT score |
term_column |
identifies term name |
dl_indicator |
identifies diverse learner status |
ell_indicator |
identifies English Language Learner status |
school_indicator |
column that identifies school |
fall_equate_scores |
either a data.frame of fall MAP results with columns 'studentid', 'measurementscale', 'testritscore', and 'grade', or 'TRUE' if your equateding all fall scores from fall-to-spring map data. If a data.frame is passed, then these data are used to equate missing pre-test (i.e., prior-spring) RIT scores per CPS guidelines. IF 'TRUE' is passed, then all fall scores are equated to the prior spring |
percent_cr |
percent of students who make excatly KIPP Tiered
college ready growth. This parameter is a scalar between in (0,1)
and is passed to |
This function essentially creates a two season CDF where
the second, later season has anticipated results. The resulting
CDF is suitable for passing to school_growth_percentile
and after filtering to the second season to school_attainment_percentile
.
The percent_cr
is used to control the minimum pernctage
of students in the CDF that make KIPP Tiered college ready
growth. Students not picked to make CR ready growth have growth that
drawn from rnorm
with the mean and sd set by
for each student the 2011 NWEA MAP student-level norms.
Since CR students are identified rbinom
and
non CR growth is determeind by rnorm
these
project growth of of students is fundametnally stochastic.
Consequently, this function is best suited for simulating
growth.
As with school_growth_percentile
, you can pass single
season CDF of fall results to impute prior spring scores for students
list with four data frames attached showing student-, grade-, and school-level growth percentiles as well as the original data.
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