ORTH.Ord: Alternating Logistic Regression with Orthogonalized Residuals
for Correlated Ordinal Outcomes
A modified version of alternating logistic regressions (ALR) with estimation based on orthogonalized residuals (ORTH) is implemented, which use paired estimating equations to jointly estimate parameters in marginal mean and within-association models. The within-cluster association between ordinal responses is modeled by global pairwise odds ratios (POR). A finite-sample bias correction is provided to POR parameter estimates based on matrix multiplicative adjusted orthogonalized residuals (MMORTH) for correcting estimating equations, and different bias-corrected variance estimators such as BC1, BC2, and BC3.
| Version: |
1.0.1 |
| Depends: |
R (≥ 4.0), magic, MASS |
| Suggests: |
knitr, rmarkdown |
| Published: |
2024-08-26 |
| Author: |
Can Meng  [aut,
cre],
Fan Li [aut] |
| Maintainer: |
Can Meng <can.meng at yale.edu> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
ORTH.Ord results |
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