thresholds {eRm} | R Documentation |
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