The R Journal: article published in 2016, volume 8:2

multipleNCC: Inverse Probability Weighting of Nested Case-Control Data
Nathalie C. Støer and Sven Ove Samuelsen , The R Journal (2016) 8:2, pages 5-18.

Abstract Reuse of controls from nested case-control designs can increase efficiency in many situations, for instance with competing risks or in other multiple endpoints situations. The matching between cases and controls must be broken when controls are to be used for other endpoints. A weighted analysis can then be performed to take care of the biased sampling from the cohort. We present the R package multipleNCC for reuse of controls in nested case-control studies by inverse probability weighting of the partial likelihood. The package handles right-censored, left-truncated and additionally matched data, and varying numbers of sampled controls and the whole analysis is carried out using one simple command. Four weight estimators are presented and variance estimation is explained. The package is illustrated by analyzing health survey data from three counties in Norway for two causes of death: cardiovascular disease and death from alcohol abuse, liver disease, and accidents and violence. The data set is included in the package.

Received: 2015-08-23; online 2016-08-11
CRAN packages: multipleNCC, survival, mgcv, ipw, MatchIt, NestedCohort, survey, Epi, gam
CRAN Task Views implied by cited CRAN packages: SocialSciences, Survival, Econometrics, Environmetrics, OfficialStatistics, Bayesian, ClinicalTrials

This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2016-030,
  author = {Nathalie C. Støer and Sven Ove Samuelsen},
  title = {{multipleNCC: Inverse Probability Weighting of Nested Case-
          Control Data}},
  year = {2016},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2016-030},
  url = {https://doi.org/10.32614/RJ-2016-030},
  pages = {5--18},
  volume = {8},
  number = {2}
}