gtsummary
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ddsjoberg
Feature Request: tbl_svysummary() support with replicate weight survey design
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tbl_svysummary() returns an error with replicate weight survey design. I am not terribly familiar with how the survey package interfaces with gtsummary these packages are new to me. Apologies if I've missed something in the documentation. Working with a new-to-me script that supposedly ran at one point and no longer does.
Notes:
I can get tbl_svysummary() to work on the same dataset without replicate weights (using a standard survey object), as well as with tbl_summary() and the raw data. Reprex is from the sample here: https://r-survey.r-forge.r-project.org/survey/html/svrepdesign.html.
library(survey)
#> Loading required package: grid
#> Loading required package: Matrix
#> Loading required package: survival
#>
#> Attaching package: 'survey'
#> The following object is masked from 'package:graphics':
#>
#> dotchart
library(gtsummary)
data(scd)
# use BRR replicate weights from Levy and Lemeshow
repweights<-2*cbind(c(1,0,1,0,1,0), c(1,0,0,1,0,1), c(0,1,1,0,0,1),
c(0,1,0,1,1,0))
scdrep<-svrepdesign(data=scd, type="BRR", repweights=repweights, combined.weights=FALSE)
#> Warning in svrepdesign.default(data = scd, type = "BRR", repweights =
#> repweights, : No sampling weights provided: equal probability assumed
scdrep |>
tbl_svysummary(
by = ambulance,
include = c(
arrests
)
)
#> Warning in svrVar(repmeans, scale, rscales, mse = design$mse, coef = rval): 1
#> replicates gave NA results and were discarded.
#> Error in `mutate()`:
#> ! Problem while computing `df_stats = pmap(...)`.
#> Caused by error in `pmap()`:
#> ℹ In index: 1.
#> Caused by error in `set_names()`:
#> ! The size of `nm` (4) must be compatible with the size of `x` (3).
#> Backtrace:
#> ▆
#> 1. ├─gtsummary::tbl_svysummary(scdrep, by = ambulance, include = c(arrests))
#> 2. │ └─gtsummary:::generate_metadata(...)
#> 3. │ └─meta_data %>% ...
#> 4. ├─dplyr::mutate(...)
#> 5. ├─dplyr:::mutate.data.frame(...)
#> 6. │ └─dplyr:::mutate_cols(.data, dplyr_quosures(...), caller_env = caller_env())
#> 7. │ ├─base::withCallingHandlers(...)
#> 8. │ └─mask$eval_all_mutate(quo)
#> 9. ├─purrr::pmap(...)
#> 10. │ └─purrr:::pmap_("list", .l, .f, ..., .progress = .progress)
#> 11. │ ├─purrr:::with_indexed_errors(...)
#> 12. │ │ └─base::withCallingHandlers(...)
#> 13. │ └─gtsummary (local) .f(...)
#> 14. │ └─gtsummary (local) df_stats_function(...)
#> 15. │ └─gtsummary:::summarize_categorical_survey(...)
#> 16. │ └─... %>% ...
#> 17. ├─rlang::set_names(., c("by", "variable_levels", "p", "p.std.error"))
#> 18. └─rlang::abort(message = message)
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.2.2 (2022-10-31)
#> os macOS Monterey 12.6
#> system aarch64, darwin20
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/New_York
#> date 2023-01-09
#> pandoc 2.19.2 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.2.0)
#> broom.helpers 1.11.0 2023-01-06 [1] CRAN (R 4.2.2)
#> cli 3.5.0 2022-12-20 [1] CRAN (R 4.2.0)
#> colorspace 2.0-3 2022-02-21 [1] CRAN (R 4.2.0)
#> DBI 1.1.3 2022-06-18 [1] CRAN (R 4.2.0)
#> digest 0.6.31 2022-12-11 [1] CRAN (R 4.2.0)
#> dplyr 1.0.10 2022-09-01 [1] CRAN (R 4.2.0)
#> ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.2.0)
#> evaluate 0.19 2022-12-13 [1] CRAN (R 4.2.0)
#> fansi 1.0.3 2022-03-24 [1] CRAN (R 4.2.0)
#> fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.2.0)
#> forcats 0.5.2 2022-08-19 [1] CRAN (R 4.2.0)
#> fs 1.5.2 2021-12-08 [1] CRAN (R 4.2.0)
#> generics 0.1.3 2022-07-05 [1] CRAN (R 4.2.0)
#> ggplot2 3.4.0 2022-11-04 [1] CRAN (R 4.2.0)
#> glue 1.6.2 2022-02-24 [1] CRAN (R 4.2.0)
#> gt 0.8.0 2022-11-16 [1] CRAN (R 4.2.0)
#> gtable 0.3.1 2022-09-01 [1] CRAN (R 4.2.0)
#> gtsummary * 1.6.3 2022-12-06 [1] CRAN (R 4.2.0)
#> highr 0.10 2022-12-22 [1] CRAN (R 4.2.0)
#> htmltools 0.5.4 2022-12-07 [1] CRAN (R 4.2.0)
#> knitr 1.41 2022-11-18 [1] CRAN (R 4.2.0)
#> lattice 0.20-45 2021-09-22 [1] CRAN (R 4.2.2)
#> lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.2.0)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.2.0)
#> Matrix * 1.5-1 2022-09-13 [1] CRAN (R 4.2.2)
#> mitools 2.4 2019-04-26 [1] CRAN (R 4.2.0)
#> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.2.0)
#> pillar 1.8.1 2022-08-19 [1] CRAN (R 4.2.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.2.0)
#> purrr 1.0.0 2022-12-20 [1] CRAN (R 4.2.0)
#> R6 2.5.1 2021-08-19 [1] CRAN (R 4.2.0)
#> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.2.0)
#> rlang 1.0.6 2022-09-24 [1] CRAN (R 4.2.0)
#> rmarkdown 2.18 2022-11-09 [1] CRAN (R 4.2.0)
#> rstudioapi 0.14 2022-08-22 [1] CRAN (R 4.2.0)
#> scales 1.2.1 2022-08-20 [1] CRAN (R 4.2.0)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.2.0)
#> stringi 1.7.8 2022-07-11 [1] CRAN (R 4.2.0)
#> stringr 1.5.0 2022-12-02 [1] CRAN (R 4.2.0)
#> survey * 4.1-1 2021-07-19 [1] CRAN (R 4.2.0)
#> survival * 3.4-0 2022-08-09 [1] CRAN (R 4.2.2)
#> tibble 3.1.8 2022-07-22 [1] CRAN (R 4.2.0)
#> tidyr 1.2.1 2022-09-08 [1] CRAN (R 4.2.0)
#> tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.2.0)
#> utf8 1.2.2 2021-07-24 [1] CRAN (R 4.2.0)
#> vctrs 0.5.1 2022-11-16 [1] CRAN (R 4.2.0)
#> withr 2.5.0 2022-03-03 [1] CRAN (R 4.2.0)
#> xfun 0.36 2022-12-21 [1] CRAN (R 4.2.0)
#> yaml 2.3.6 2022-10-18 [1] CRAN (R 4.2.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/library
#>
#> ──────────────────────────────────────────────────────────────────────────────
Created on 2023-01-09 with reprex v2.0.2
Looks like this is because the svrepdesign() function does not append a period after se so the following code never finds a condition for "p.std.error", which results in not enough columns for set_names() after the pivot_wider() call.
mutate(
stat = if_else(
str_starts(.data$name, paste0("se.", variable)) | str_starts(.data$name, paste0("se.`", variable, "`")),
"p.std.error",
"p"
),
That is great investigatory work!
Are you interested in submitting a pull requst? @larmarange are you open to an update that would handle svrepdesign() objects as well?
I'm not sure if I quite understand the the pieces going into the code enough but I will take a look. I also realized that the svrepdesign() returns something like se1 instead of se.variableName so there's an additional bit of re-attaching the variable name as well.
Are you interested in submitting a pull requst? @larmarange are you open to an update that would handle
svrepdesign()objects as well?
No problem. 😊
Great, I'll leave this open until someone is inspired to submit a pull request 😝
Hi @larmarange and @rbcavanaugh ,
Reviewing some of the lingering issues and wanted to give an update. In order to make this work, we'd need to have a version of each of the functions listed here to work with replicate weights designs. https://insightsengineering.github.io/cardx/main/reference/index.html#-survey-package
I think this would be a big undertaking and no one has jumped on it yet. I am going to go ahead and close this issue. But if anyone in the future wants to make the effort, please reach out before getting started.