View source: R/item_discrimination.R
item_discrimination | R Documentation |
Compute various measures of internal consistencies for tests or item-scales of questionnaires.
item_discrimination(x, standardize = FALSE)
x |
A matrix or a data frame. |
standardize |
Logical, if |
This function calculates the item discriminations (corrected item-total
correlations for each item of x
with the remaining items) for each item
of a scale. The absolute value of the item discrimination indices should be
above 0.2
. An index between 0.2
and 0.4
is considered as "fair", while a
satisfactory index ranges from 0.4
to 0.7
. Items with low discrimination
indices are often ambiguously worded and should be examined. Items with
negative indices should be examined to determine why a negative value was
obtained (e.g. reversed answer categories regarding positive and negative
poles).
A data frame with the item discrimination (corrected item-total correlations) for each item of the scale.
Kelava A, Moosbrugger H (2020). Deskriptivstatistische Itemanalyse und Testwertbestimmung. In: Moosbrugger H, Kelava A, editors. Testtheorie und Fragebogenkonstruktion. Berlin, Heidelberg: Springer, 143–158
data(mtcars)
x <- mtcars[, c("cyl", "gear", "carb", "hp")]
item_discrimination(x)
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