RCI | R Documentation |
Computes an IRT version of the "reliable change index" (RCI) proposed by Jacobson and Traux (1991) but modified to use IRT information about scores and measurement error. Main benefit of the IRT approach is the inclusion of response pattern information in the pre/post data score estimates, as well as conditional standard error of measurement information.
RCI(mod, predat, postdat, cutoffs = NULL, ...)
mod |
single-group model fitted by |
predat |
a vector (if one individual) or matrix/data.frame of response data to be scored, where each individuals' responses are included in exactly one row |
postdat |
same as |
cutoffs |
optional vector of length 2 indicating the type of cut-offs to
report (e.g., |
... |
additional arguments passed to |
Phil Chalmers rphilip.chalmers@gmail.com
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v048.i06")}
Jacobson, N. S., & Truax, P. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59, 12-19.
## Not run:
mod <- mirt(Science, 1)
# single response pattern change using EAP information
RCI(mod, predat = c(1,2,3,2), postdat = c(1,2,2,1))
# WLE estimator
RCI(mod, predat = c(1,2,3,2), postdat = c(1,2,2,1), method = 'WLE')
# multiple respondents
RCI(mod, predat = Science[1:5,], postdat = Science[2:6,])
# include large-sample z-type cutoffs
RCI(mod, predat = Science[1:5,], postdat = Science[2:6,],
cutoffs = c(-1.96, 1.96))
############################
# Example where individuals take completely different item set pre-post
# but prior calibration has been performed to equate the items
dat <- key2binary(SAT12,
key = c(1,4,5,2,3,1,2,1,3,1,2,4,2,1,5,3,4,4,1,4,3,3,4,1,3,5,1,3,1,5,4,5))
mod <- mirt(dat, 1)
# with N=5 individuals under investigation
predat <- postdat <- dat[1:5,]
predat[, 17:32] <- NA
postdat[, 1:16] <- NA
head(predat)
head(postdat)
RCI(mod, predat, postdat)
## End(Not run)
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