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

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

Arguments

Arguments for thresholds:

object

Object of class eRm.

Arguments for print, summary, and confint methods:

x

Object of class threshold.

parm

Parameter specification (ignored).

level

Alpha-level.

...

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

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).

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.

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

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#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

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