CLCM
Estimate Confirmatory Latent Class Models
Estimate confirmatory latent class models for a variety of item response types that are encountered in the clinical field. One or two timepoints are supported. Latent regression estimation can be performed, allowing for comparisons of longitudinal latent class assignments (e.g., treatment success/failure) across observed groups (e.g., treatment arms in clinical trials). Fit statistics C2 (a limited-information goodness-of-fit statistic), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) are available as well. Methods are described in Iaconangelo (2026) <doi:10.5281/zenodo.22663151>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling linux/jammy R-4.5 | CLCM_0.1.1.tar.gz |
205.9 KiB |
0.1.1 |
rolling linux/noble R-4.5 | CLCM_0.1.1.tar.gz |
205.8 KiB |
0.1.1 |
rolling source/ R- | CLCM_0.1.1.tar.gz |
140.7 KiB |
0.1.1 |
latest linux/jammy R-4.5 | CLCM_0.1.1.tar.gz |
205.9 KiB |
0.1.1 |
latest linux/noble R-4.5 | CLCM_0.1.1.tar.gz |
205.8 KiB |
0.1.1 |
latest source/ R- | CLCM_0.1.1.tar.gz |
140.7 KiB |
0.1.1 |
2026-04-23 source/ R- | CLCM_0.1.1.tar.gz |
0 B |