ICC {TestGardener} | R Documentation |
Plotting probability and surprisal curves for an item
Description
This is an S3 object that contains information essential plotting probability and surprisal curves for a single multiple choice or rating question. Bin probabilities and surprisal values can also be plotted.
Usage
ICC(x, M, Sfd, Zmat, Pbin, Sbin, Pmatfine, Smatfine, DSmatfine, D2Smatfine,
PStdErr, SStdErr, ItemArcLen, itemStr=NULL, optStr=NULL)
Arguments
x |
An item number. |
M |
The number of options for this item, including an option for missing or illegal values if required. |
Sfd |
A functional surprisal curve object defined by |
Zmat |
An |
Pbin |
A |
Sbin |
A |
Pmatfine |
A 101 by |
Smatfine |
A 101 by |
DSmatfine |
A 101 by |
D2Smatfine |
A 101 by |
PStdErr |
A 101 by |
SStdErr |
A 101 by |
ItemArcLen |
The scope or arc length of the item curve. |
itemStr |
A string that is the name of the item. |
optStr |
A character vector containing labels for the item options. |
Details
The name ICC for this object is an acronym for the term "item characteristic curve" widely used in the psychometric commuunity.
Function ICC is set up after the initialization process in function
make_dataList()
has created the members of dataList
.
Within this list is object SfdList
, which cintains a functional data
object Sfd
for each item. Both the intial coefficient matrices and
the subsequent estimates of them are available from Sfd$coefs
, and
therefore are available in the ICC object. These coefficient matrices are
K
by M-1
where K
is the number of basis functions and
M
is the number of options for asn item.
Value
The values returned are simply those in the argument list. The S3
ICC object checks each of these and makes available the S3 commands or methods
str
, print
and plot
that apply the corresponding
ICC
versions of these opterations.
Author(s)
Juan Li and James Ramsay
References
Ramsay, J. O., Li J. and Wiberg, M. (2020) Full information optimal scoring. Journal of Educational and Behavioral Statistics, 45, 297-315.
Ramsay, J. O., Li J. and Wiberg, M. (2020) Better rating scale scores with information-based psychometrics. Psych, 2, 347-360.