I have been trying to figure out the equivalent syntax for rstanarm::stan_jm in brms as I’m more confident in my ability to modify brms programs than I am with rstanarm . I’ve been able to get syntax that works, but returns very different results, suggesting that the brms implementation is doing something different (or incorrectly).
The stan_jm model is:
f1 <- stan_jm(formulaLong = logBili ~ year + (1 | id),
dataLong = pbcLong,
formulaEvent = Surv(futimeYears, death) ~ sex + trt,
dataEvent = pbcSurv,
time_var = "year",
# this next line is only to keep the example small in size!
chains = 1, cores = 1, seed = 12345, iter = 1000, basehaz = "weibull")
My attempt at a brms implementation (based on an embarrassing amount of asking chatGPT):
#combine the pbcLong and pbcSurve data into a single dataframe for brms
tst <- merge(pbcLong, pbcSurv)
brms_joint <- brm(
formula = bf(logBili ~ year + (1 | id)) + # Longitudinal model for log(bili)
bf(futimeYears | cens(1 - status) ~ sex +trt, family = weibull()), # Survival model using Weibull distribution
data = tst,
chains = 2, cores = 2, iter = 3000, seed = 12345,
prior = prior,
control = list(adapt_delta = 0.95)
)
I can’t tell whether the syntax in the brms model is using a different association structure (or how I would change that). Or perhaps it is not possible to fit such a model in brms (maybe @Solomon has already tried this)? The results of the two models are not just numerically different, but would lead to substantially different conclusions.
Thanks for any suggestions ou can give.
- Operating System: MacOS Sonoma 14.7.2
- brms Version:2.22.0
sessionInfo(package = NULL)
R version 4.4.0 (2024-04-24)
Platform: x86_64-apple-darwin20
Running under: macOS Sonoma 14.7.2
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/Boise
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] rstanarm_2.32.1 survival_3.5-8 brms_2.22.0 Rcpp_1.0.13
loaded via a namespace (and not attached):
[1] tidyselect_1.2.1 dplyr_1.1.4 loo_2.8.0 fastmap_1.2.0
[5] tensorA_0.36.2.1 shinystan_2.6.0 promises_1.3.0 shinyjs_2.1.0
[9] digest_0.6.37 mime_0.12 lifecycle_1.0.4 StanHeaders_2.32.10
[13] processx_3.8.4 magrittr_2.0.3 posterior_1.6.0 compiler_4.4.0
[17] rlang_1.1.5 tools_4.4.0 igraph_2.1.1 utf8_1.2.4
[21] data.table_1.15.4 bridgesampling_1.1-2 htmlwidgets_1.6.4 pkgbuild_1.4.4
[25] curl_5.2.3 plyr_1.8.9 dygraphs_1.1.1.6 pkgload_1.3.4
[29] abind_1.4-8 miniUI_0.1.1.1 grid_4.4.0 stats4_4.4.0
[33] fansi_1.0.6 xts_0.14.0 xtable_1.8-4 colorspace_2.1-1
[37] inline_0.3.19 ggplot2_3.5.1 MASS_7.3-60.2 scales_1.3.0
[41] gtools_3.9.5 cli_3.6.4 mvtnorm_1.2-5 generics_0.1.3
[45] RcppParallel_5.1.9 rstudioapi_0.16.0 reshape2_1.4.4 minqa_1.2.8
[49] rstan_2.32.7 stringr_1.5.1 shinythemes_1.2.0 splines_4.4.0
[53] bayesplot_1.11.1 parallel_4.4.0 matrixStats_1.4.1 base64enc_0.1-3
[57] vctrs_0.6.5 boot_1.3-30 V8_4.4.2 Matrix_1.7-0
[61] jsonlite_1.8.9 callr_3.7.6 crosstalk_1.2.1 glue_1.8.0
[65] nloptr_2.1.1 codetools_0.2-20 ps_1.8.0 DT_0.33
[69] distributional_0.5.0 stringi_1.8.4 gtable_0.3.6 later_1.3.2
[73] QuickJSR_1.3.1 lme4_1.1-35.5 munsell_0.5.1 tibble_3.2.1
[77] colourpicker_1.3.0 pillar_1.9.0 htmltools_0.5.8.1 Brobdingnag_1.2-9
[81] R6_2.5.1 shiny_1.9.1 lattice_0.22-6 markdown_1.13
[85] backports_1.5.0 threejs_0.3.3 httpuv_1.6.15 rstantools_2.4.0
[89] coda_0.19-4.1 gridExtra_2.3 nlme_3.1-164 checkmate_2.3.2
[93] zoo_1.8-12 pkgconfig_2.0.3