Package: ODS 0.2.0
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>.
Authors:
ODS_0.2.0.tar.gz
ODS_0.2.0.zip(r-4.5)ODS_0.2.0.zip(r-4.4)ODS_0.2.0.zip(r-4.3)
ODS_0.2.0.tgz(r-4.4-any)ODS_0.2.0.tgz(r-4.3-any)
ODS_0.2.0.tar.gz(r-4.5-noble)ODS_0.2.0.tar.gz(r-4.4-noble)
ODS_0.2.0.tgz(r-4.4-emscripten)ODS_0.2.0.tgz(r-4.3-emscripten)
ODS.pdf |ODS.html✨
ODS/json (API)
| # Install 'ODS' in R: |
| install.packages('ODS', repos = c('https://yinghao-pan.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/yinghao-pan/ods/issues
- casecohort_data_secondary - Data example for the secondary analysis in case-cohort design
- ods_data - Data example for analyzing the primary response in ODS design
- ods_data_secondary - Data example for the secondary analysis in ODS design
Last updated 6 years agofrom:af4dd7fe22. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 10 2024 |
| R-4.5-win | OK | Sep 10 2024 |
| R-4.5-linux | OK | Sep 10 2024 |
| R-4.4-win | OK | Sep 10 2024 |
| R-4.4-mac | OK | Sep 10 2024 |
| R-4.3-win | OK | Sep 10 2024 |
| R-4.3-mac | OK | Sep 10 2024 |
Exports:BfctEstimate_PLMODSgcv_ODSlogspaceodsmlequantileknotsse.spmlesecondary_casecohortsecondary_ODS
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| power basis functions of a spline of given degree | Bfct |
| Data example for the secondary analysis in case-cohort design | casecohort_data_secondary |
| Partial linear model for ODS data | Estimate_PLMODS |
| Generalized cross-validation for ODS data | gcv_ODS |
| Generate logarithmically spaced vector | logspace |
| Data example for analyzing the primary response in ODS design | ods_data |
| Data example for the secondary analysis in ODS design | ods_data_secondary |
| MSELE estimator for analyzing the primary outcome in ODS design | odsmle |
| Create knots at sample quantiles | quantileknots |
| standard error for MSELE estimator | se.spmle |
| Secondary analysis in case-cohort data | secondary_casecohort |
| Secondary analysis in ODS design | secondary_ODS |
