Testing the ISOP Model
This function performs tests of the W1 axiom of the ISOP model (Scheiblechner, 2003). Standard errors of the corresponding W1_i statistics are obtained by Jackknife.
isop.test(data, jackunits=20, weights=rep(1, nrow(data))) ## S3 method for class 'isop.test' summary(object,...)
data |
Data frame with item responses |
jackunits |
A number of Jackknife units (if an integer is provided as the argument value) or a vector in the Jackknife units are already defined. |
weights |
Optional vector of sampling weights |
object |
Object of class |
... |
Further arguments to be passed |
A list with following entries
itemstat |
Data frame with test and item statistics for the W1 axiom.
The W1_i statistic is denoted as |
Es |
Number of concordances per item |
Ed |
Number of disconcordances per item |
The W1_i statistics are printed by the summary method.
Scheiblechner, H. (2003). Nonparametric IRT: Testing the bi-isotonicity of isotonic probabilistic models (ISOP). Psychometrika, 68, 79-96.
See also the ISOP package at Rforge: http://www.rforge.net/ISOP/.
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# EXAMPLE 1: ISOP model data.Students
#############################################################################
data(data.Students, package="CDM")
dat <- data.Students[, paste0("act",1:5) ]
dat <- dat[1:300, ] # select first 300 students
# perform the ISOP test
mod <- sirt::isop.test(dat)
summary(mod)
## -> W1i statistics
## parm N M est se t
## 1 test 300 NA 0.430 0.036 11.869
## 2 act1 278 0.601 0.451 0.048 9.384
## 3 act2 275 0.473 0.473 0.035 13.571
## 4 act3 274 0.277 0.352 0.098 3.596
## 5 act4 291 1.320 0.381 0.054 7.103
## 6 act5 276 0.460 0.475 0.042 11.184Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.