Package: hesim 0.5.5
hesim: Health Economic Simulation Modeling and Decision Analysis
A modular and computationally efficient R package for parameterizing, simulating, and analyzing health economic simulation models. The package supports cohort discrete time state transition models (Briggs et al. 1998) <doi:10.2165/00019053-199813040-00003>, N-state partitioned survival models (Glasziou et al. 1990) <doi:10.1002/sim.4780091106>, and individual-level continuous time state transition models (Siebert et al. 2012) <doi:10.1016/j.jval.2012.06.014>, encompassing both Markov (time-homogeneous and time-inhomogeneous) and semi-Markov processes. Decision uncertainty from a cost-effectiveness analysis is quantified with standard graphical and tabular summaries of a probabilistic sensitivity analysis (Claxton et al. 2005, Barton et al. 2008) <doi:10.1002/hec.985>, <doi:10.1111/j.1524-4733.2008.00358.x>. Use of C++ and data.table make individual-patient simulation, probabilistic sensitivity analysis, and incorporation of patient heterogeneity fast.
Authors:
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hesim.pdf |hesim.html✨
hesim/json (API)
# Install 'hesim' in R: |
install.packages('hesim', repos = c('https://hesim-dev.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/hesim-dev/hesim/issues
- mstate3_exdata - Example data for a reversible 3-state multi-state model
- multinom3_exdata - Example data for a 3-state multinomial model
- onc3 - Multi-state oncology data for 3-state model
- onc3p - Multi-state panel oncology data for 3-state model
- psm4_exdata - Example data for a 4-state partitioned survival model
health-economic-evaluationmicrosimulationsimulation-modeling
Last updated 2 months agofrom:bb52350051. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 17 2024 |
R-4.5-win-x86_64 | OK | Nov 17 2024 |
R-4.5-linux-x86_64 | OK | Nov 17 2024 |
R-4.4-win-x86_64 | OK | Nov 17 2024 |
R-4.4-mac-x86_64 | OK | Nov 17 2024 |
R-4.4-mac-aarch64 | OK | Nov 17 2024 |
R-4.3-win-x86_64 | OK | Nov 17 2024 |
R-4.3-mac-x86_64 | OK | Nov 17 2024 |
R-4.3-mac-aarch64 | OK | Nov 17 2024 |
Exports:apply_rras_array3as_pfs_osas_tbl2as.data.tableautoplotceacea_pwCohortDtstmCohortDtstmTranscreate_CohortDtstmcreate_CohortDtstmTranscreate_IndivCtstmTranscreate_input_matscreate_lines_dtcreate_paramscreate_PsmCurvescreate_StateValscreate_trans_dtCtstmTransdefine_modeldefine_rngdefine_tparamsdweibullNMAeval_modeleval_rngexpandexpmatfast_rgengammaflexsurvreg_listformula_listget_labelshesim_datahesim_survdistshweibullNMAHweibullNMAiceaicea_pwicericer_tblid_attributesincr_effectIndivCtstmIndivCtstmTransinput_matslm_listmean_weibullNMAmom_betamom_gammamultinom_listparams_lmparams_mlogitparams_mlogit_listparams_survparams_surv_listpartsurvfitplot_ceacplot_ceafplot_ceplaneplot_evpiPsmPsmCurvespweibullNMAqmatrixqweibullNMArcatrdirichlet_matrmst_weibullNMArpwexprweibullNMAset_labelssim_costssim_evsim_qalyssim_stateprobsstateval_tblStateValssurv_quantilesurvivaltime_intervalstparams_meantparams_transprobstpmatrixtpmatrix_idtpmatrix_names
Dependencies:assertthatbbmlebdsmatrixBHclicolorspacecpp11data.tabledeSolvedplyrexpmfansifarverfastGHQuadflexsurvgenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmsmmstatemuhazmunsellmvtnormnlmenumDerivpillarpkgconfigpurrrquadprogR6RColorBrewerRcppRcppArmadillorlangrstpm2scalesstatmodstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr
Cost-effectiveness analysis
Rendered fromcea.Rmd
usingknitr::rmarkdown
on Nov 17 2024.Last update: 2021-02-15
Started: 2020-09-17
Introduction to hesim
Rendered fromintro.Rmd
usingknitr::rmarkdown
on Nov 17 2024.Last update: 2021-02-17
Started: 2018-05-19
Markov and semi-Markov multi-state models
Rendered frommstate.Rmd
usingknitr::rmarkdown
on Nov 17 2024.Last update: 2021-07-25
Started: 2020-03-09
Markov models with multinomial logistic regression
Rendered frommlogit.Rmd
usingknitr::rmarkdown
on Nov 17 2024.Last update: 2021-07-09
Started: 2020-02-29
Partitioned survival models
Rendered frompsm.Rmd
usingknitr::rmarkdown
on Nov 17 2024.Last update: 2021-03-06
Started: 2018-07-30
Simple Markov cohort model
Rendered frommarkov-cohort.Rmd
usingknitr::rmarkdown
on Nov 17 2024.Last update: 2021-02-15
Started: 2020-09-17
Time inhomogeneous Markov cohort models
Rendered frommarkov-inhomogeneous-cohort.Rmd
usingknitr::rmarkdown
on Nov 17 2024.Last update: 2021-02-15
Started: 2020-09-17
Time inhomogeneous Markov individual-level models
Rendered frommarkov-inhomogeneous-indiv.Rmd
usingknitr::rmarkdown
on Nov 17 2024.Last update: 2022-03-30
Started: 2020-09-17