Add a column to a data frame of student-level records that indicates the latest term by which degree completion would be considered timely for every student.
Arguments
- dframe
Working data frame of student-level records to which timely-term columns are to be added. Required variable is
mcid.- midfield_term
MIDFIELD
termdata table or equivalent with required variablesmcid,term, andlevel.- ...
Not used for passing values; forces subsequent arguments to be referable only by name.
- span
Optional integer scalar, number of years to define timely completion. Commonly used values are are 100, 150, and 200 percent of
sched_span.Default 6 years.- sched_span
Optional integer scalar, the number of years an institution officially schedules for completing a program. Default 4 years.
Value
A data frame in data.table format with the following
properties: rows are preserved; columns are preserved with the exception
that columns added by the function overwrite existing columns of the
same name (if any); grouping structures are not preserved. The added
columns are:
term_iCharacter. Initial term of a student's longitudinal record, encoded YYYYT
level_iCharacter. Student level (01 Freshman, 02 Sophomore, etc.) in their initial term
adj_spanNumeric. Integer span of years for timely completion adjusted for a student's initial level.
timely_termCharacter. Latest term by which program completion would be considered timely for every student. Encoded YYYYT.
Details
By "completion" we mean an undergraduate earning their first baccalaureate degree (or degrees, for students earning more than one degree in the same term).
In many studies, students must complete their programs in a specified time span, for example 4-, 6-, or 8-years after admission. If they do, their completion is timely; if not, their completion is late and they are grouped with the non-completers when computing a metric such as graduation rate.
Our heuristic assigns span number of years (default is 6 years) to every
student. For students admitted at second-year level or higher, the span is
reduced by one year for each full year the student is assumed to have
completed. For example, a student admitted at the second-year level is
assumed to have completed one year of a program, so their span is reduced by
one year.
The adjusted span is added to the initial term to create the timely
completion term in the timely_term column.
See also
Other add_*:
add_completion_status(),
add_data_sufficiency()
Examples
# Start with an excerpt from the student data set
dframe <- toy_student[1:10, .(mcid)]
# Add timely completion term column
add_timely_term(dframe, midfield_term = toy_term)
#> mcid term_i level_i adj_span timely_term
#> <char> <char> <char> <num> <char>
#> 1: MID25784187 19885 01 Freshman 6 19943
#> 2: MID25784974 19883 02 Sophomore 5 19931
#> 3: MID25816209 19881 02 Sophomore 5 19923
#> 4: MID25819358 19946 02 Sophomore 5 19993
#> 5: MID25828870 19881 01 Freshman 6 19933
#> 6: MID25829749 19995 03 Junior 4 20033
#> 7: MID25841418 19981 03 Junior 4 20013
#> 8: MID25845197 19905 03 Junior 4 19943
#> 9: MID25846316 19911 01 Freshman 6 19963
#> 10: MID25847220 19891 01 Freshman 6 19943
# Define timely completion as 200% of scheduled span (8 years)
add_timely_term(dframe, midfield_term = toy_term, span = 8)
#> mcid term_i level_i adj_span timely_term
#> <char> <char> <char> <num> <char>
#> 1: MID25784187 19885 01 Freshman 8 19963
#> 2: MID25784974 19883 02 Sophomore 7 19951
#> 3: MID25816209 19881 02 Sophomore 7 19943
#> 4: MID25819358 19946 02 Sophomore 7 20013
#> 5: MID25828870 19881 01 Freshman 8 19953
#> 6: MID25829749 19995 03 Junior 6 20053
#> 7: MID25841418 19981 03 Junior 6 20033
#> 8: MID25845197 19905 03 Junior 6 19963
#> 9: MID25846316 19911 01 Freshman 8 19983
#> 10: MID25847220 19891 01 Freshman 8 19963
# Existing timely_term column, if any, is overwritten
dframe[, timely_term := NA_character_]
#> mcid timely_term
#> <char> <char>
#> 1: MID25784187 <NA>
#> 2: MID25784974 <NA>
#> 3: MID25816209 <NA>
#> 4: MID25819358 <NA>
#> 5: MID25828870 <NA>
#> 6: MID25829749 <NA>
#> 7: MID25841418 <NA>
#> 8: MID25845197 <NA>
#> 9: MID25846316 <NA>
#> 10: MID25847220 <NA>
add_timely_term(dframe, midfield_term = toy_term)
#> mcid term_i level_i adj_span timely_term
#> <char> <char> <char> <num> <char>
#> 1: MID25784187 19885 01 Freshman 6 19943
#> 2: MID25784974 19883 02 Sophomore 5 19931
#> 3: MID25816209 19881 02 Sophomore 5 19923
#> 4: MID25819358 19946 02 Sophomore 5 19993
#> 5: MID25828870 19881 01 Freshman 6 19933
#> 6: MID25829749 19995 03 Junior 4 20033
#> 7: MID25841418 19981 03 Junior 4 20013
#> 8: MID25845197 19905 03 Junior 4 19943
#> 9: MID25846316 19911 01 Freshman 6 19963
#> 10: MID25847220 19891 01 Freshman 6 19943