logistic4p
Logistic Regression with Misclassification in Dependent Variables
Error in a binary dependent variable, also known as misclassification, has not drawn much attention in psychology. Ignoring misclassification in logistic regression can result in misleading parameter estimates and statistical inference. This package conducts logistic regression analysis with misspecification in outcome variables.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.6 |
rolling linux/jammy R-4.5 | logistic4p_1.6.tar.gz |
83.0 KiB |
1.6 |
rolling linux/noble R-4.5 | logistic4p_1.6.tar.gz |
83.0 KiB |
1.6 |
rolling source/ R- | logistic4p_1.6.tar.gz |
33.7 KiB |
1.6 |
latest linux/jammy R-4.5 | logistic4p_1.6.tar.gz |
83.0 KiB |
1.6 |
latest linux/noble R-4.5 | logistic4p_1.6.tar.gz |
83.0 KiB |
1.6 |
latest source/ R- | logistic4p_1.6.tar.gz |
33.7 KiB |
1.6 |
2026-04-26 source/ R- | logistic4p_1.6.tar.gz |
33.7 KiB |
1.6 |
2026-04-23 source/ R- | logistic4p_1.6.tar.gz |
33.7 KiB |
1.6 |
2026-04-09 windows/windows R-4.5 | logistic4p_1.6.zip |
86.2 KiB |
1.6 |
2025-04-20 source/ R- | logistic4p_1.6.tar.gz |
33.7 KiB |