efficiency {optical} | R Documentation |
Efficiency of optimal design
Description
This function computes the efficiency of the D, I, and A optimal designs compared to the random design.
Usage
efficiency(
yyy,
ip,
uncert = FALSE,
ipop,
oc = "D",
L = NULL,
items = FALSE,
integ = TRUE
)
Arguments
yyy |
|
ip |
matrix with item parameters for all items (number of rows determines number of items; number of columns is 2 (for 2PL; or 1PL with common a-parameter when NA in first column from second item) or 3 (for 3PL; or mixed 2/3-PL with NA for 2PL-items in third column) |
uncert |
if false (default), abilities are assumed to be known; if true, handling of uncertainties of Bjermo et al. (2021) is used. |
ipop |
matrix with item parameters for operational items (used if uncert=TRUE, only). |
oc |
optimality criterion: "D" (D-optimality, default), "I" (I-optimality with standard normal weight function), "A" (A-optimality). |
L |
L-matrix (not used for D-optimality) |
items |
if false (default), only total block efficiency is returned; if true, criteria for optimal and random and the efficiency for each item are reported in each column of output. Last column are then total criteria and efficiency. D-, L-, I-, A-optimality |
integ |
if true (default), integrate() is used for computation of partial information matrices; if false, Riemann rule is used. |
Value
A numerical value is displayed.
See Also
Examples
# 2PL-models for two items; parameters (a, b)=(1.6, -1) and (1.6, 1), respectively
ip <- cbind(c(1.6, 1.6),c(-1, 1))
yyy <- optical(ip)
# Efficiency of A-optimal design compared to random design
efficiency(yyy, ip, oc="A")
# Efficiency of D-optimal design compared to random design
efficiency(yyy, ip, oc="D")
# Efficiency of I-optimal design compared to random design
efficiency(yyy, ip, oc="I")