A key is a set of difficulty estimates linked to items from one or more instruments. As more data become available, the key may be updated periodically to incorporate the additional information. This results in multiple versions of the key. Although keys are designed to produce D-scores on the same general scale, each key defines a slightly different scale. As a result, the same set of child responses may yield different D-scores depending on which key is used.
For new data, the most recent default key is usually recommended. However, if strict comparability with earlier analyses is important, it may be preferable to use an older key.
This vignette explains the policy for setting default keys and demonstrates how to compare D-scores across different keys. Because this is an advanced topic, it assumes a basic understanding of the D-score calculation process. If you are new to the D-score methodology, we recommend reviewing the introductory vignettes before proceeding.
Describe how the default key is chosen (e.g., most recent stable release) and how often it is updated. State where users can find the current default in the package documentation.
Show users how to enumerate supported keys.
Demonstrate how to select a specific key in your workflow.
Show the same dataset scored under two keys and compare.
Provide simple diagnostics to understand differences (plots/tables).
Discuss empirical evidence (e.g., median absolute difference, 95% intervals) showing that differences across keys are generally small.
## R version 4.5.1 (2025-06-13)
## Platform: aarch64-apple-darwin20
## Running under: macOS Tahoe 26.0.1
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## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.1
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## locale:
## [1] C/C.UTF-8/C.UTF-8/C/C.UTF-8/C.UTF-8
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## time zone: Europe/Amsterdam
## tzcode source: internal
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## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
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## other attached packages:
## [1] lme4_1.1-37 Matrix_1.7-3 ggplot2_4.0.0 dplyr_1.1.4 dscore_2.0.0
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## loaded via a namespace (and not attached):
## [1] sass_0.4.10 generics_0.1.4 tidyr_1.3.1 xml2_1.4.0
## [5] stringi_1.8.7 lattice_0.22-7 digest_0.6.37 magrittr_2.0.3
## [9] evaluate_1.0.5 grid_4.5.1 RColorBrewer_1.1-3 fastmap_1.2.0
## [13] jsonlite_2.0.0 purrr_1.1.0 viridisLite_0.4.2 scales_1.4.0
## [17] textshaping_1.0.3 jquerylib_0.1.4 Rdpack_2.6.4 reformulas_0.4.1
## [21] cli_3.6.5 rlang_1.1.6 rbibutils_2.3 splines_4.5.1
## [25] withr_3.0.2 cachem_1.1.0 yaml_2.3.10 tools_4.5.1
## [29] nloptr_2.2.1 minqa_1.2.8 boot_1.3-31 kableExtra_1.4.0
## [33] vctrs_0.6.5 R6_2.6.1 lifecycle_1.0.4 stringr_1.5.2
## [37] MASS_7.3-65 pkgconfig_2.0.3 pillar_1.11.0 bslib_0.9.0
## [41] gtable_0.3.6 glue_1.8.0 Rcpp_1.1.0 systemfonts_1.2.3
## [45] xfun_0.53 tibble_3.3.0 tidyselect_1.2.1 rstudioapi_0.17.1
## [49] knitr_1.50 farver_2.1.2 htmltools_0.5.8.1 nlme_3.1-168
## [53] rmarkdown_2.29 svglite_2.2.1 labeling_0.4.3 compiler_4.5.1
## [57] S7_0.2.0