| Name : R-ODS
| |
| Version : 0.2.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.3.7
| Date : 2024-06-14 11:24:47
|
| Group : Development/Libraries/Other
| Source RPM : R-ODS-0.2.0-lp153.3.7.src.rpm
|
| Size : 0.24 MB
| |
| Packager : (none)
| |
| Summary : Statistical Methods for Outcome-Dependent Sampling Designs
|
Description :
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>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
