student | R Documentation |
Student-level demographic information for approximately 98,000 degree-seeking undergraduate students, keyed by student ID. Data at the "student-level" refers to information collected by undergraduate institutions about individual students, for example, age, sex, and race/ethnicity at matriculation.
data(student)
A data.frame
and data.table
with 13 variables and 97,555
observations of unique students occupying 18 MB of memory:
mcid
Character, anonymized student identifier, e.g., MCID3111142225
.
institution
Character, de-identified institution name, e.g., Institution A, Institution B, etc.
transfer
Character, transfer status, possible values are
First-Time in College
, First-Time Transfer
.
hours_transfer
Numeric, number of credit hours transferred (or
NA
).
race
Character, race/ethnicity as self-reported by the student, e.g., Asian, Black, Latine, etc.
sex
Character, sex as self-reported by the student, possible values are Female, Male, and Unknown.
age_desc
Character, age group, possible values are 25 and Older
,
Under 25
.
us_citizen
Character, US citizenship, possible values are No
,
Yes
.
home_zip
Character, home ZIP code (or NA
), e.g., 02056
,
20170
, 51301
, 80129
, etc.
high_school
Character, code for the last high school attended before
admission (or NA
), e.g., 060075
, 210512
, 431800
, 502195
,
etc.
sat_math
Numeric, SAT mathematics test score (or NA
).
sat_verbal
Numeric, SAT reading test score (or NA
).
act_comp
Numeric, ACT composite test score (or NA
).
Student data are structured in row-record form, that is, information associated with a particular ID occupies a single row—one record per student.
The data in midfielddata
are a proportionate stratified sample of the
MIDFIELD database, but are not suitable for drawing inferences about program
attributes or student experiences—midfielddata
provides practice data,
not research data.
2022 MIDFIELD database
Package midfieldr
for
tools and methods for working with MIDFIELD data in R
.
Other datasets:
course
,
degree
,
term
## Not run:
# Load data
data(student)
# Select specific rows and columns
rows_we_want <- student$mcid == MCID3112192438
cols_we_want <- c(mcid, institution, transfer, race, sex, age_desc)
# View observations for this ID
student[rows_we_want, cols_we_want]
## End(Not run)
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