26,730 simulated responses from 990 respondents to 27 items.
Simulated data. These responses were generated by a script, not collected from people; see the generating script. The cov_true_appropriateness, cov_true_multiplicative_comparison, cov_true_partitioning_iterating, cov_true_referent_units columns hold the true generating values, which a real dataset would not have.
| Description | Simulated cognitive diagnosis data modeled on the Diagnosing Teachers' Multiplicative Reasoning (DTMR) assessment (990 respondents, 27 binary items, 4 attributes); not the real DTMR responses. Generated from the LCDM. True attribute profiles are in cov_true_*, true item parameters (intercept, main effects, one interaction) in itemcov_true_*, and the Q-matrix in qmatrix1-4. |
|---|---|
| Reference | Thompson W (2026). dcmdata: Data Sets for Diagnostic Classification Modeling. R package version 0.2.0. https://CRAN.R-project.org/package=dcmdata. Simulated from parameters in Bradshaw, L., Izsák, A., Templin, J., & Jacobson, E. (2014). Diagnosing teachers' understandings of rational numbers: Building a multidimensional test within the diagnostic classification framework. Educational Measurement: Issues and Practice, 33(1), 2-14, and Izsák, A., Jacobson, E., & Bradshaw, L. (2019). Surveying middle-grades teachers' reasoning about fraction arithmetic in terms of measured quantities. Journal for Research in Mathematics Education, 50(2), 156-209. |
| DOI | 10.32614/CRAN.package.dcmdata |
| Licence | MIT |
| Generating script | https://cran.r-project.org/package=dcmdata |
| Responses | 26,730 |
|---|---|
| Respondents | 990 |
| Items | 27 |
| Response categories | 2 |
| Responses per respondent | 27 |
| Responses per item | 990 |
| Density | 1 |
cov_true_appropriatenesscov_true_multiplicative_comparisoncov_true_partitioning_iteratingcov_true_referent_unitsiditemitemcov_true_appropriatenessitemcov_true_interceptitemcov_true_multiplicative_comparisonitemcov_true_partitioning_iteratingitemcov_true_referent_unitsitemcov_true_referent_units__partitioning_iteratingqmatrix1qmatrix2qmatrix3qmatrix4resp
id, item, resp are defined in the IRW data standard and mean the same in every table. The other columns are set by the generating script.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("dtmr_sim", source = "sim")
# Python
pip install irw
import irw
df = irw.fetch("dtmr_sim", source="sim")
@misc{Thompson_2025, title={dcmdata: Data Sets for Diagnostic Classification Modeling}, url={http://dx.doi.org/10.32614/CRAN.package.dcmdata}, DOI={10.32614/cran.package.dcmdata}, journal={CRAN: Contributed Packages}, publisher={The R Foundation}, author={Thompson, W. Jake}, year={2025}, month=Aug }
| IRW version | v581 |
|---|---|
| Redivis dataset | irw_simsyn v1.4 |
| Redivis dataset DOI | 10.57761/d90d-aa22 |
| Manifest pin for this IRW version | v1.4 |
| Metadata source | irw_meta v44.0 |