Dexter
Dexter is an R package for psychometric analysis of data from educational and psychological tests. Dexter typically works with project database files saved on disk.
Installation
install.packages('dexter')
If you encounter a bug, please post a minimal reproducible example on github. We post news and examples on a blog, it’s also the place for general questions.
Example
library(dexter)
# start a project and fill it with data
# verbAggrRules and verbAggrData are example datasets provided with dexter
db = start_new_project(verbAggrRules, "verbAggression.db")
add_booklet(db, verbAggrData, booklet_id = "verb_agg")
# Classical test theory
tia = tia_tables(db)
tia$testStats
verb_agg |
24 |
0.888 |
0.339 |
0.527 |
0.468 |
48 |
316 |
verb_agg |
S1DoCurse |
1.082 |
0.807 |
2 |
0.541 |
0.582 |
0.519 |
316 |
verb_agg |
S1DoScold |
0.832 |
0.815 |
2 |
0.416 |
0.651 |
0.596 |
316 |
verb_agg |
S1DoShout |
0.468 |
0.709 |
2 |
0.234 |
0.520 |
0.460 |
316 |
verb_agg |
S1WantCurse |
1.123 |
0.827 |
2 |
0.562 |
0.537 |
0.468 |
316 |
verb_agg |
S1WantScold |
0.930 |
0.850 |
2 |
0.465 |
0.593 |
0.528 |
316 |
verb_agg |
S1WantShout |
0.712 |
0.777 |
2 |
0.356 |
0.529 |
0.464 |
316 |
# IRT, extended nominal response model
f = fit_enorm(db)
head(coef(f))
S1DoCurse |
1 |
-1.3422140 |
0.1541565 |
S1DoCurse |
2 |
-0.6375015 |
0.1418423 |
S1DoScold |
1 |
-0.6702036 |
0.1429057 |
S1DoScold |
2 |
-0.2589855 |
0.1579467 |
S1DoShout |
1 |
0.3254326 |
0.1480166 |
S1DoShout |
2 |
0.3687574 |
0.2099654 |
# ability estimates per person
abl = ability(db, parms = f)
head(abl)
verb_agg |
dx_0000001 |
13 |
-1.0238738 |
verb_agg |
dx_0000002 |
28 |
0.3124831 |
verb_agg |
dx_0000003 |
4 |
-2.3748882 |
verb_agg |
dx_0000004 |
19 |
-0.4630604 |
verb_agg |
dx_0000005 |
7 |
-1.7721275 |
verb_agg |
dx_0000006 |
25 |
0.0512826 |
# ability estimates without item S1DoScold
abl2 = ability(db, parms = f, item_id != "S1DoScold")
# plausible values
pv = plausible_values(db, parms = f, nPV = 5)
head(pv)
verb_agg |
dx_0000001 |
13 |
-1.1405958 |
-1.1403792 |
-1.3288514 |
-1.0057263 |
-0.8747812 |
verb_agg |
dx_0000002 |
28 |
0.1046548 |
0.4573575 |
0.6570475 |
0.4719364 |
0.5919885 |
verb_agg |
dx_0000003 |
4 |
-1.8610768 |
-2.4363771 |
-1.9468633 |
-1.6463484 |
-2.1789387 |
verb_agg |
dx_0000004 |
19 |
-0.2334495 |
-0.1251249 |
0.0542683 |
-0.4702052 |
-0.4926505 |
verb_agg |
dx_0000005 |
7 |
-2.3289604 |
-1.7940483 |
-1.2847597 |
-1.5881818 |
-1.5760550 |
verb_agg |
dx_0000006 |
25 |
-0.5562045 |
-0.4116060 |
-0.2187003 |
-0.3003845 |
0.0500288 |