Package: xhaz 2.0.2
Juste Goungounga
xhaz:Excess Hazard Modelling Considering Inappropriate Mortality Rates
Fits relative survival regression models with or without proportional excess hazards and with the additional possibility to correct for background mortality by one or more parameter(s). These models are relevant when the observed mortality in the studied group is not comparable to that of the general population or in population-based studies where the available life tables used for net survival estimation are insufficiently stratified. In the latter case, the proposed model by Touraine et al. (2020) <doi:10.1177/0962280218823234> can be used. The user can also fit a model that relaxes the proportional expected hazards assumption considered in the Touraine et al. excess hazard model. This extension was proposed by Mba et al. (2020) <doi:10.1186/s12874-020-01139-z> to allow non-proportional effects of the additional variable on the general population mortality. In non-population-based studies, researchers can identify non-comparability source of bias in terms of expected mortality of selected individuals. An excess hazard model correcting this selection bias is presented in Goungounga et al. (2019) <doi:10.1186/s12874-019-0747-3>. This class of model with a random effect at the cluster level on excess hazard is presented in Goungounga et al. (2023) <doi:10.1002/bimj.202100210>.
Authors:
xhaz_2.0.2.tar.gz
xhaz_2.0.2.tar.gz(r-4.5-noble)xhaz_2.0.2.tar.gz(r-4.4-noble)
xhaz_2.0.2.tgz(r-4.4-emscripten)xhaz_2.0.2.tgz(r-4.3-emscripten)
xhaz.pdf |xhaz.html✨
xhaz/json (API)
| # Installxhaz in R: |
| install.packages('xhaz',repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- breast - Simulated clinical trial data with non comparability bias in term of individuals expected hazard
- ccr.mevents - Colorectum cancer data with multiple events
- dataCancer - Simulated data with cause death information with non comparability bias in term of individuals expected hazard
- rescaledData - Simulated data with cause death information with non comparability bias in term of individuals expected hazard
- simuData - Simulated data with cause death information in long term follow-up setting without non comparability bias in term of individuals expected hazard
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 days agofrom:801a061d36
Exports:duplicateexphazmexhazLTqbsxhaz
Dependencies:cligluegtoolslamWlatticelifecyclemagrittrMASSMatrixmexhaznumDerivoptimParallelRcppRcppParallelrlangstatmodstringistringrsurvexp.frsurvivalvctrsWriteXLS
Introduction to Excess Hazard Modelling Considering Inappropriate Mortality Rates
Rendered fromintroduction.Rmdusingknitr::rmarkdownon Jun 30 2024.Last update: 2024-06-30
Started: 2022-09-07
How to implement a rescaled random-effects excess hazard regression model to handle situations involving inappropriate life tables.
Rendered fromrescaling_excess_hazard_models.Rmdusingknitr::rmarkdownon Jun 30 2024.Last update: 2024-06-30
Started: 2024-06-30
