Bug: Cannot reorder residual SD for mixed effects models
mccarthy-m-g opened this issue · 5 comments
The coef_map argument is unable to reorder the residual SD for mixed effects models; the residual SD is always forced to the bottom. Here's a reprex:
library(modelsummary)
library(lme4)
sleepstudy_fit <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
# Bug: The residual SD is always forced to the bottom of the estimates section.
modelsummary(
sleepstudy_fit,
coef_map = c("SD (Observations)", "(Intercept)")
)| (1) | |
|---|---|
| (Intercept) | 251.405 |
| (6.825) | |
| SD (Observations) | 25.592 |
# As a consequence, it's impossible to group all the residuals together in the
# table.
modelsummary(
sleepstudy_fit,
coef_map = c(
"SD (Intercept Subject)",
"SD (Days Subject)",
"SD (Observations)",
"Cor (Intercept~Days Subject)"
)
)| (1) | |
|---|---|
| SD (Intercept Subject) | 24.741 |
| SD (Days Subject) | 5.922 |
| Cor (Intercept~Days Subject) | 0.066 |
| SD (Observations) | 25.592 |
Created on 2024-04-23 with reprex v2.0.2
Session info:
R version 4.2.2 (2022-10-31)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Mojave 10.14.6
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale:
[1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] lme4_1.1-35.2 Matrix_1.6-4 modelsummary_2.0.0 devtools_2.4.5
[5] usethis_2.1.6
loaded via a namespace (and not attached):
[1] Rcpp_1.0.11 lattice_0.20-45 listenv_0.9.1 ps_1.7.5
[5] utf8_1.2.4 digest_0.6.33 mime_0.12 parallelly_1.36.0
[9] R6_2.5.1 backports_1.4.1 reprex_2.0.2 evaluate_0.23
[13] pillar_1.9.0 rlang_1.1.2 rstudioapi_0.14 minqa_1.2.6
[17] data.table_1.15.4 miniUI_0.1.1.1 performance_0.11.0 callr_3.7.3
[21] nloptr_2.0.3 urlchecker_1.0.1 checkmate_2.3.1 effectsize_0.8.6
[25] rmarkdown_2.25 splines_4.2.2 stringr_1.5.1 htmlwidgets_1.6.4
[29] shiny_1.7.4 compiler_4.2.2 httpuv_1.6.7 xfun_0.43
[33] pkgconfig_2.0.3 parameters_0.21.6 pkgbuild_1.4.3 clipr_0.8.0
[37] globals_0.16.3 htmltools_0.5.7 insight_0.19.10 tibble_3.2.1
[41] codetools_0.2-18 fansi_1.0.6 future_1.33.2 withr_3.0.0
[45] later_1.3.0 tables_0.9.25 MASS_7.3-58.1 grid_4.2.2
[49] nlme_3.1-160 xtable_1.8-4 lifecycle_1.0.4 magrittr_2.0.3
[53] bayestestR_0.13.2 datawizard_0.10.0 future.apply_1.11.2 cli_3.6.2
[57] stringi_1.8.3 cachem_1.0.8 fs_1.6.3 promises_1.2.0.1
[61] remotes_2.4.2 ellipsis_0.3.2 generics_0.1.3 vctrs_0.6.5
[65] boot_1.3-28 tools_4.2.2 tinytable_0.2.1 glue_1.6.2
[69] purrr_1.0.2 processx_3.8.3 yaml_2.3.8 pkgload_1.3.4
[73] parallel_4.2.2 fastmap_1.1.1 sessioninfo_1.2.2 memoise_2.0.1
[77] knitr_1.45 profvis_0.3.7 I'm new to using modelsummary so I'm still familiarizing myself with it, but I believe the issue here is that the residual SD and other variance components have different group identifiers, which prevents the desired reordering.
get_estimates(sleepstudy_fit)
term estimate std.error conf.level conf.low conf.high
1 (Intercept) 251.40510485 6.824597 0.95 237.935457 264.8748
2 Days 10.46728596 1.545790 0.95 7.416374 13.5182
3 SD (Intercept Subject) 24.74065800 NA 0.95 NA NA
4 SD (Days Subject) 5.92213766 NA 0.95 NA NA
5 Cor (Intercept~Days Subject) 0.06555124 NA 0.95 NA NA
6 SD (Observations) 25.59179572 NA 0.95 NA NA
statistic df.error p.value effect group s.value
1 36.838090 174 4.372791e-84 fixed 276.9
2 6.771481 174 1.882719e-10 fixed 32.3
3 NA NA NA random Subject NA
4 NA NA NA random Subject NA
5 NA NA NA random Subject NA
6 NA NA NA random Residual NANote that changing the shape argument to use different group identifiers will make the desired reordering possible (e.g., shape = term + effect + statistic ~ model). So I guess the issue at hand is whether or not this could be the default for mixed models, rather than the present default. Not exactly a bug, but still unexpected behaviour that appears bug-like at first.
Yep, I think you're diagnostic is correct. You can use group_map to change the order of groups.
That said, I do agree that this is counterintuitive. I pushed a commit to Github. If you install it an restart R, you’ll get this:
library(lme4)
library(modelsummary)
sleepstudy_fit <- lmer(Reaction ~ Days + I(Days^2) + (Days | Subject), sleepstudy)
modelsummary(
sleepstudy_fit,
coef_map = c("SD (Observations)", "(Intercept)", "Days")
)| SD (Observations) | 25.534 |
| (Intercept) | 255.449 |
| (7.514) | |
| Days | 7.434 |
| (2.819) | |
| Num.Obs. | 180 |
| R2 Marg. | 0.280 |
| R2 Cond. | 0.800 |
| AIC | 1756.8 |
| BIC | 1779.2 |
| ICC | 0.7 |
| RMSE | 23.30 |
Thanks Vincent, great package by the way!
Glad you like it!