ODS: Statistical Methods for Outcome-Dependent Sampling Designs

Outcome-dependent sampling (ODS) schemes are cost-effective ways to enhance study efficiency. In ODS designs, one observes the exposure/covariates with a probability that depends on the outcome variable. Popular ODS designs include case-control for binary outcome, case-cohort for time-to-event outcome, and continuous outcome ODS design (Zhou et al. 2002) <doi:10.1111/j.0006-341X.2002.00413.x>. Because ODS data has biased sampling nature, standard statistical analysis such as linear regression will lead to biases estimates of the population parameters. This package implements four statistical methods related to ODS designs: (1) An empirical likelihood method analyzing the primary continuous outcome with respect to exposure variables in continuous ODS design (Zhou et al., 2002). (2) A partial linear model analyzing the primary outcome in continuous ODS design (Zhou, Qin and Longnecker, 2011) <doi:10.1111/j.1541-0420.2010.01500.x>. (3) Analyze a secondary outcome in continuous ODS design (Pan et al. 2018) <doi:10.1002/sim.7672>. (4) An estimated likelihood method analyzing a secondary outcome in case-cohort data (Pan et al. 2017) <doi:10.1111/biom.12838>.

Version: 0.2.0
Depends: R (≥ 3.5.0)
Imports: cubature (≥ 1.4-1), survival (≥ 2.42-3), utils, stats
Published: 2018-11-19
Author: Yinghao Pan [aut, cre], Haibo Zhou [aut], Mark Weaver [aut], Guoyou Qin [aut], Jianwen Cai [aut]
Maintainer: Yinghao Pan <ypan8 at uncc.edu>
BugReports: https://github.com/Yinghao-Pan/ODS/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/Yinghao-Pan/ODS
NeedsCompilation: no
Materials: README
CRAN checks: ODS results

Downloads:

Reference manual: ODS.pdf
Package source: ODS_0.2.0.tar.gz
Windows binaries: r-devel: ODS_0.2.0.zip, r-release: ODS_0.2.0.zip, r-oldrel: ODS_0.2.0.zip
OS X binaries: r-release: ODS_0.2.0.tgz, r-oldrel: ODS_0.2.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ODS to link to this page.