Computation of item-category treshold parameters.
This function transforms the beta parameters into threshold parameters. These can be interpreted by means of log-odds as visualized in ICC plots.
## 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 for thresholds:
object |
Object of class |
Arguments for print, summary, and confint methods:
x |
Object of class |
parm |
Parameter specification (ignored). |
level |
Alpha-level. |
... |
Further arguments to be passed to methods. They are ignored. |
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).
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. |
Andrich, D. (1978). Application of a psychometric rating model to ordered categories which are scored with successive integers. Applied Psychological Measurement, 2, 581-594.
#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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