| Name : R-CIEE
| |
| Version : 0.1.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : 2.48
| Date : 2024-08-05 21:30:50
|
| Group : Development/Libraries/Other
| Source RPM : R-CIEE-0.1.1-2.48.src.rpm
|
| Size : 0.48 MB
| |
| Packager : (none)
| |
| Summary : Estimating and Testing Direct Effects in Directed Acyclic Graphs using Estimating Equations
|
Description :
In many studies across different disciplines, detailed measures of the
variables of interest are available. If assumptions can be made
regarding the direction of effects between the assessed variables, this
has to be considered in the analysis. The functions in this package
implement the novel approach CIEE (causal inference using estimating
equations; Konigorski et al., 2018, < DOI:10.1002/gepi.22107>) for
estimating and testing the direct effect of an exposure variable on a
primary outcome, while adjusting for indirect effects of the exposure
on the primary outcome through a secondary intermediate outcome and
potential factors influencing the secondary outcome. The underlying
directed acyclic graph (DAG) of this considered model is described in
the vignette. CIEE can be applied to studies in many different fields,
and it is implemented here for the analysis of a continuous primary
outcome and a time-to-event primary outcome subject to censoring. CIEE
uses estimating equations to obtain estimates of the direct effect and
robust sandwich standard error estimates. Then, a large-sample
Wald-type test statistic is computed for testing the absence of the
direct effect. Additionally, standard multiple regression, regression
of residuals, and the structural equation modeling approach are
implemented for comparison.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/x86_64 |
