eRm (version 1.0-1)

thresholds: Computation of item-category treshold parameters.

Description

This function transforms the beta parameters into threshold parameters. These can be interpreted by means of log-odds as visualized in ICC plots.

Usage

# S3 method for eRm
thresholds(object)
# S3 method for threshold
print(x, ...)
# S3 method for threshold
summary(object, ...)
# S3 method for threshold
confint(object, parm, level = 0.95, ...)

Arguments

object

Object of class eRm.

x

Object of class threshold.

parm

Parameter specification (ignored).

level

Alpha-level.

...

Further arguments to be passed to methods. They are ignored.

Value

The function thresholds returns an object of class threshold containing:

threshpar

Vector with threshold parameters.

se.thresh

Vector with standard errors.

threshtable

Data frame with location and threshold parameters.

Details

For dichotomous models (i.e., RM and LLTM) threshold parameters are not computed. The print method returns a location parameter for each item which is the mean of the corresponding threshold parameters. For LPCM and LRSM the thresholds are computed for each design matrix block (i.e., measurement point/group) separately (PCM and RSM have only 1 block).

References

Andrich, D. (1978). Application of a psychometric rating model to ordered categories which are scored with successive integers. Applied Psychological Measurement, 2, 581-594.

See Also

plotICC.Rm

Examples

# NOT RUN {
#Threshold parameterization for a rating scale model
res <- RSM(rsmdat)
th.res <- thresholds(res)
th.res
confint(th.res)
summary(th.res)

#Threshold parameters for a PCM with ICC plot
res <- PCM(pcmdat)
th.res <- thresholds(res)
th.res
plotICC(res)

#Threshold parameters for a LPCM:
#Block 1: t1, g1; Block 2: t1, g2; ...; Block 6: t2,g3
G <- c(rep(1,7),rep(2,7),rep(3,6)) # group vector for 3 groups
res <- LPCM(lpcmdat, mpoints = 2, groupvec = G)
th.res <- thresholds(res)
th.res
# }