data.read

This dataset contains \(N=328\) students and \(I=12\) items measuring reading
competence. All 12 items are arranged into 3 testlets (items with common
text stimulus) labeled as
A, B and C. The allocation of items to testlets is indicated by their
variable names.

Supplementary functions for item response models aiming
to complement existing R packages. The functionality includes among others
multidimensional compensatory and noncompensatory IRT models
(Reckase, 2009, <doi:10.1007/978-0-387-89976-3>),
MCMC for hierarchical IRT models and testlet models
(Fox, 2010, <doi:10.1007/978-1-4419-0742-4>),
NOHARM (McDonald, 1982, <doi:10.1177/014662168200600402>),
Rasch copula model (Braeken, 2011, <doi:10.1007/s11336-010-9190-4>;
Schroeders, Robitzsch & Schipolowski, 2014, <doi:10.1111/jedm.12054>),
faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011,
<doi:10.1111/j.1745-3984.2011.00143.x>),
ordinal IRT model (ISOP; Scheiblechner, 1995, <doi:10.1007/BF02301417>),
DETECT statistic (Stout, Habing, Douglas & Kim, 1996,
<doi:10.1177/014662169602000403>), local structural equation modeling
(LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016,
<doi:10.1080/00273171.2016.1142856>).

Alexander Robitzsch

sirt

Supplementary Item Response Theory Models

data.read function

A data frame with 328 persons on the following 12 variables.
 Rows correspond to persons and columns to items. The following items are
 included in <code>data.read</code>:
Testlet A: <code>A1</code>, <code>A2</code>, <code>A3</code>, <code>A4</code>
Testlet B: <code>B1</code>, <code>B2</code>, <code>B3</code>, <code>B4</code>
Testlet C: <code>C1</code>, <code>C2</code>, <code>C3</code>, <code>C4</code>

data.read: Dataset Reading

Description

Usage

Arguments

Format