Package: PAmeasures 2.0.0.9000

PAmeasures: Performance Assessment for Continuous and Survival Outcomes

Evaluates prediction accuracy for continuous outcomes and the predictive performance of survival models in a unified framework. Implements the R-squared, L-squared, pseudo R-squared and related explained variation measures of Li and Wang (2019) <doi:10.1080/01621459.2018.1515079>, the concordance indices of Harrell et al. (1982) <doi:10.1001/jama.1982.03320430047030> and Uno et al. (2011) <doi:10.1002/sim.4154>, the time-dependent area under the receiver operating characteristic curve (AUC) of Heagerty, Lumley and Pepe (2000) <doi:10.1111/j.0006-341X.2000.00337.x>, and the Brier score of Graf et al. (1999) <doi:10.1002/(SICI)1097-0258(19990915/30)18:17/18%3C2529::AID-SIM274%3E3.0.CO;2-5>. Supports right-censored data; competing risks, following Wolbers et al. (2014) <doi:10.1093/biostatistics/kxt059>, Wu and Li (2018) <doi:10.1002/sim.7806> and Zhuang et al. (2025) <doi:10.48550/arXiv.2507.15040>; and two-phase sampling designs such as case-cohort and nested case-control studies, following Lee, Zeleniuch-Jacquotte and Liu (2021) <doi:10.1080/02664763.2020.1861225>. Revives and expands the original 'PAmeasures' package with a unified interface for survival prediction assessment.

Authors:Tong Zhu [aut], Zian Zhuang [aut, cre], Wen Su [aut], Xiaowu Dai [aut], Xiaoyan Wang [aut], Gang Li [aut]