Package: resilience 2024.1.2

resilience: Predictors of Resilience to a Stressor in a Single-Arm Study

Studies of resilience in older adults employ a single-arm design where everyone experiences the stressor. The simplistic approach of regressing change versus baseline yields biased estimates due to regression-to-the-mean. This package provides a method to correct the bias. It also allows covariates to be included. The method implemented in the package is described in Varadhan, R., Zhu, J., and Bandeen-Roche, K (2023), Biostatistics (To appear).

Authors:Ravi Varadhan [aut, cre], Jiafeng Zhu [ctb]

resilience_2024.1.2.tar.gz
resilience_2024.1.2.zip(r-4.5)resilience_2024.1.2.zip(r-4.4)resilience_2024.1.2.zip(r-4.3)
resilience_2024.1.2.tgz(r-4.4-any)resilience_2024.1.2.tgz(r-4.3-any)
resilience_2024.1.2.tar.gz(r-4.5-noble)resilience_2024.1.2.tar.gz(r-4.4-noble)
resilience_2024.1.2.tgz(r-4.4-emscripten)resilience_2024.1.2.tgz(r-4.3-emscripten)
resilience.pdf |resilience.html✨
resilience/json (API)

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1 exports 0.36 score 5 dependencies 3 scripts 227 downloads

Last updated 26 days agofrom:cf50196390. Checks:OK: 7. Indexed: yes.

Exports:prepost

Dependencies:codetoolsdoParallelforeachiteratorsnptest