Standard Error of Measurement (IRT).

Estimate the standard error of measurement in item response theory.

Usage

standardErrorIRT(information)

Arguments

information

Test information.

Value

Standard error of measurement for that amount of test information.

Details

Estimate the standard error of measurement in item response theory using the test information (i.e., the sum of all items' information).

See also

doi:10.1177/0146621613475471

Other IRT: deriv_d_negBinom(), discriminationToFactorLoading(), fourPL(), itemInformation(), reliabilityIRT(), test_info_4PL()

Examples

# Calculate information for 4 items
item1 <- itemInformation(b = -2, a = 0.6, theta = -4:4)
item2 <- itemInformation(b = -1, a = 1.2, theta = -4:4)
item3 <- itemInformation(b = 1, a = 1.5, theta = -4:4)
item4 <- itemInformation(b = 2, a = 2, theta = -4:4)

items <- data.frame(item1, item2, item3, item4)

# Calculate test information
items$testInformation <- rowSums(items)

# Calculate standard error of measurement
standardErrorIRT(items$testInformation)
#> [1] 3.1220949 2.2478963 1.6396572 1.3436736 1.1732756 0.9381903 0.8450600
#> [8] 1.3489596 3.0432995