R/interaction_model.R
fit_domains.Rd
Estimate the parameters of the Rasch model and the Interaction model
fit_domains(dataSrc, item_property, predicate = NULL)
a connection to a dexter database or a data.frame with columns: person_id, item_id, item_score
The item property defining the domains (subtests)
An optional expression to subset data, if NULL all data is used
An object of class imp
holding results
for the Rasch model and the interaction model.
We have generalised the interaction model for items having more than two (potentially, a largish number) of response categories. This function represents scores on subtests as super-items and analyses these as normal items.
db = start_new_project(verbAggrRules, ":memory:")
add_booklet(db, verbAggrData, "agg")
#> no column `person_id` provided, automatically generating unique person id's
#> $items
#> [1] "S1DoCurse" "S1DoScold" "S1DoShout" "S1WantCurse" "S1WantScold"
#> [6] "S1WantShout" "S2DoCurse" "S2DoScold" "S2DoShout" "S2WantCurse"
#> [11] "S2WantScold" "S2WantShout" "S3DoCurse" "S3DoScold" "S3DoShout"
#> [16] "S3WantCurse" "S3WantScold" "S3WantShout" "S4DoCurse" "S4DoScold"
#> [21] "S4DoShout" "S4WantCurse" "S4WantScold" "S4WantShout"
#>
#> $person_properties
#> character(0)
#>
#> $columns_ignored
#> [1] "gender" "anger"
#>
add_item_properties(db, verbAggrProperties)
#> 4 item properties for 24 items added or updated
mSit = fit_domains(db, item_property= "situation")
plot(mSit)
close_project(db)