What alignment adds | Compact matrix workflow | Interpretation and diagnostics
Package: PsychoMatic 1.0.1
PsychoMatic: Automated Psychometric Workflows and Reporting Tools
Automates common psychometric workflows for applied researchers, including item descriptives, inter-item correlations, exploratory and confirmatory factor analysis, exploratory structural equation measurement models, reliability, psychometric network analysis, multi-group measurement invariance, and alignment optimization. Decision heuristics are informed by procedures such as parallel analysis (Horn, 1965, <doi:10.1007/BF02289447>), multivariate normality diagnostics (Mardia, 1970, <doi:10.1093/biomet/57.3.519>), measurement-invariance fit-change rules (Chen, 2007, <doi:10.1080/10705510701301834>), and alignment optimization (Asparouhov and Muthen, 2014, <doi:10.1080/10705511.2014.919210>), among others. Results can be returned as structured R objects and exported as bilingual reports for transparent analytical documentation.
Authors:
PsychoMatic_1.0.1.tar.gz
PsychoMatic_1.0.1.zip(r-4.7-any)PsychoMatic_1.0.1.zip(r-4.6-any)PsychoMatic_1.0.1.zip(r-4.5-any)
PsychoMatic_1.0.1.tgz(r-4.6-any)PsychoMatic_1.0.1.tgz(r-4.5-any)
PsychoMatic_1.0.1.tar.gz(r-4.7-any)PsychoMatic_1.0.1.tar.gz(r-4.6-any)
PsychoMatic_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PsychoMatic/json (API)
| # Install 'PsychoMatic' in R: |
| install.packages('PsychoMatic', repos = c('https://gmoncayoj.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gmoncayoj/psychomatic/issues
confirmatory-factor-analysisexploratory-factor-analysisexploratory-structural-equations-modelinginvarianceinvariance-alignmentnetwork-psychometricspsychometricsquantitative-psychologyreliabilitystatistical-analysis
Last updated from:b61a1e5c98. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 529 | ||
| source / vignettes | OK | 560 | ||
| linux-release | OK | 644 | ||
| macos-release | OK | 480 | ||
| macos-oldrel | OK | 364 | ||
| windows-devel | OK | 293 | ||
| windows-release | OK | 690 | ||
| windows-oldrel | OK | 390 | ||
| wasm-release | OK | 311 |
Exports:cfa_autocompare_models_autocormatdesc_autodif_autoefa_autoesem_autoexport_cfaexport_efafactorial_invariance_autoinv_align_autoinvariance_partialirt_autonetwork_autonetwork_plotsordinal_invariance_autopsychomatic_reportpsychomatic_specreliability_autoreverse_itemsscore_scalescreen_items
Dependencies:GPArotationlatticelavaanMASSMatrixmnormtnlmenumDerivpbivnormpsychquadprog
Alignment Invariance Workflow
Last update: 2026-10-23
Started: 2026-06-17
Automated psychometric network analysis
Last update: 2026-10-23
Started: 2026-10-23
Complete and Partial Measurement Invariance
Complete invariance | Ordered indicators and identification | Three-stage ordinal invariance | Researcher-directed partial invariance | Which workflow comes next?
Last update: 2026-10-23
Started: 2026-06-17
Confirmatory Factor Analysis Workflow
A compact CFA | Compare models only when comparable | Reliability and model form | Conditions, precision, and migration
Last update: 2026-10-23
Started: 2026-06-17
Exploratory Factor Analysis Workflow
Prepare and check ordinal items | Reliability is not dimensionality | EFA with non-destructive screening
Last update: 2026-10-23
Started: 2026-06-17
Getting Started with PsychoMatic
Purpose | Declare the data once | Check and score | Structured evidence
Last update: 2026-10-23
Started: 2026-06-17
Measurement ESEM: target and geomin rotation
Use with your data | Choosing the rotation | Reproducible target example | Reproducible geomin example | Estimation, uncertainty and failed solutions | Final interpretation and reports | References
Last update: 2026-10-23
Started: 2026-10-23
