Introduction | Workflow overview | Workflow | Example: norming a single test | Shape the data | Fit candidate models | Inspect model fit | Create norm tables | Confidence intervals for normed scores | Advanced features | Norming of composite scores | Norms for a new sample of individuals | Norming with a truncated model | Estimating test reliability dependent on age | Sample size planning for continuous norming | References
Package: normref 0.1.2
normref: Continuous Norming
A toolbox for continuous norming of psychological and educational tests, supporting regression-based norming where norms can vary as a continuous function of age or another norm predictor. Norms are estimated using Generalized Additive Models for Location, Scale, and Shape (GAMLSS), enabling flexible modelling of the full score distribution in a normative sample. The package supports applications in psychometrics and psychological testing, and includes functions for model selection, reliability estimation, norm calculation, including confidence intervals, and sample size planning. For more details, see Timmerman et al. (2021) <doi:10.1037/met0000348>.
Authors:
normref_0.1.2.tar.gz
normref_0.1.2.zip(r-4.7-any)normref_0.1.2.zip(r-4.6-any)normref_0.1.2.zip(r-4.5-any)
normref_0.1.2.tgz(r-4.6-any)normref_0.1.2.tgz(r-4.5-any)
normref_0.1.2.tar.gz(r-4.7-any)normref_0.1.2.tar.gz(r-4.6-any)
normref_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
normref/json (API)
| # Install 'normref' in R: |
| install.packages('normref', repos = c('https://metimmerman.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- cotapp_data - Cotapp data
- ids_data - Ids data
- ids_kn_data - The ids_kn_data are simlulated data for demonstration purposes
- ids_rel_data - These fictional reliability data are for demonstration purposes.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:113187cfac. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 121 | ||
| source / vignettes | OK | 574 | ||
| linux-release | OK | 124 | ||
| macos-release | OK | 194 | ||
| macos-oldrel | OK | 190 | ||
| windows-devel | OK | 70 | ||
| windows-release | OK | 83 | ||
| windows-oldrel | OK | 74 | ||
| wasm-release | OK | 116 |
Exports:centiles_bincomposite_shapedifferent_relfb_selectnormtable_createplot_drelplot_normtablereliability_windowsample_size_polyshape_data
Dependencies:clicpp11farvergamlssgamlss.datagamlss.distggplot2gluegtableisobandlabelinglatticelifecyclelpSolveMASSMatrixnlmeopenxlsx2R6rbibutilsRColorBrewerRcppRdpackrlangS7scalesstringisurvivalvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Capture a family of distribution functions and their closures | capture_family_env |
| Plot centiles of a fitted GAMLSS model (binomial-type) | centiles_bin |
| Shape data for a composite scale based on normalized Z-scores | composite_shape |
| cotapp data | cotapp_data |
| Estimate reliability across multiple window widths and age steps | different_rel |
| Free order model selection procedure | fb_select |
| ids data | ids_data |
| The ids_kn_data are simlulated data for demonstration purposes | ids_kn_data |
| These fictional reliability data are for demonstration purposes. | ids_rel_data |
| Create a norm table based on a GAMLSS fitted model | normtable_create |
| Plot reliability estimates over age | plot_drel |
| Plot norm curves from a NormTable object | plot_normtable |
| Estimate test reliability by age using a sliding window | reliability_window |
| Sample size planning for continuous norming using polynomial regression | sample_size_poly |
| Shape data as input for 'fb_select()' | shape_data |