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easystats
`pretty_names = TRUE` do not fully work for "repeated rows"
In the table outputs of the next reprex, we should see Indirect Effect (ACME) in each file where ACME appears and the same for Direct Effect (ADE) with ADE, however, for each table they only appear in the first ACME/ADE rows. In particular I added the line attr(m, "pretty_names") <- c(attr(m20, "pretty_names"), attr(m70, "pretty_names")) to be sure the pretty_names are for all the involved rows.
library(mediation)
#> Loading required package: MASS
#> Loading required package: Matrix
#> Loading required package: mvtnorm
#> Loading required package: sandwich
#> mediation: Causal Mediation Analysis
#> Version: 4.5.0
library(parameters)
data(jobs)
# Allowing ``moderated mediation'' with respect to age
b.int <- lm(job_seek ~ treat*age + econ_hard + sex, data=jobs)
d.int <- lm(depress2 ~ treat*job_seek*age + econ_hard + sex, data=jobs)
contcont.age20 <- mediate(b.int, d.int, sims=50, treat="treat", mediator="job_seek",
covariates = list(age = 20))
contcont.age70 <- mediate(b.int, d.int, sims=50, treat="treat", mediator="job_seek",
covariates = list(age = 70))
m20 <- model_parameters(contcont.age20)
m70 <- model_parameters(contcont.age70)
m20[["age level"]] <- 20
m70[["age level"]] <- 70
m <- rbind(m20, m70)
attr(m, "pretty_names") <- c(attr(m20, "pretty_names"), attr(m70, "pretty_names"))
str(m)
#> Classes 'parameters_model', 'see_parameters_model' and 'data.frame': 20 obs. of 8 variables:
#> $ Parameter: chr "ACME (control)" "ACME (treated)" "ADE (control)" "ADE (treated)" ...
#> $ Estimate : num -0.0459 -0.0274 -0.0502 -0.0318 -0.0776 ...
#> $ CI : num 0.95 0.95 0.95 0.95 0.95 0.95 0.95 0.95 0.95 0.95 ...
#> $ CI_low : num -0.1078 -0.0656 -0.1868 -0.1682 -0.2264 ...
#> $ CI_high : num 0.00768 0.00874 0.06707 0.10573 0.06468 ...
#> $ p : num 0.12 0.12 0.48 0.68 0.36 0.32 0.32 0.12 0.56 0.32 ...
#> $ Component: chr "control" "treated" "control" "treated" ...
#> $ age level: num 20 20 20 20 20 20 20 20 20 20 ...
#> - attr(*, "object_name")= chr "contcont.age20"
#> - attr(*, "pretty_names")= Named chr [1:20] "Indirect Effect (ACME)" "Indirect Effect (ACME)" "Direct Effect (ADE)" "Direct Effect (ADE)" ...
#> ..- attr(*, "names")= chr [1:20] "ACME" "ACME" "ADE" "ADE" ...
#> - attr(*, "ci")= num 0.95
#> - attr(*, "verbose")= logi TRUE
#> - attr(*, "exponentiate")= logi FALSE
#> - attr(*, "ordinal_model")= logi FALSE
#> - attr(*, "linear_model")= logi FALSE
#> - attr(*, "mixed_model")= logi FALSE
#> - attr(*, "model_class")= chr "mediate"
#> - attr(*, "bootstrap")= logi FALSE
#> - attr(*, "iterations")= num 1000
#> - attr(*, "robust_vcov")= logi FALSE
#> - attr(*, "ignore_group")= logi TRUE
#> - attr(*, "ran_pars")= logi TRUE
#> - attr(*, "show_summary")= logi FALSE
#> - attr(*, "weighted_nobs")= num 899
#> - attr(*, "coefficient_name")= chr "Coefficient"
#> - attr(*, "zi_coefficient_name")= chr "Log-Odds"
#> - attr(*, "digits")= num 2
#> - attr(*, "ci_digits")= num 2
#> - attr(*, "p_digits")= num 3
#> - attr(*, "footer_digits")= num 3
print_md(m)
| Parameter | Estimate | 95% CI | p | age level |
|---|---|---|---|---|
| Indirect Effect (ACME) | -0.05 | (-0.11, 7.68e-03) | 0.120 | 20.00 |
| Direct Effect (ADE) | -0.05 | (-0.19, 0.07) | 0.480 | 20.00 |
| Prop. Mediated | 0.33 | (-4.73, 2.78) | 0.320 | 20.00 |
| ACME | 0.03 | (-0.06, 0.13) | 0.720 | 70.00 |
| ADE | -0.08 | (-0.34, 0.18) | 0.600 | 70.00 |
| Prop. Mediated | 0.04 | (-3.08, 5.61) | 0.880 | 70.00 |
control
| Parameter | Estimate | 95% CI | p | age level |
|---|---|---|---|---|
| Indirect Effect (ACME) | -0.03 | (-0.07, 8.74e-03) | 0.120 | 20.00 |
| Direct Effect (ADE) | -0.03 | (-0.17, 0.11) | 0.680 | 20.00 |
| Prop. Mediated | 0.25 | (-2.45, 1.33) | 0.320 | 20.00 |
| ACME | 0.02 | (-0.05, 0.10) | 0.600 | 70.00 |
| ADE | -0.09 | (-0.34, 0.16) | 0.640 | 70.00 |
| Prop. Mediated | 0.05 | (-1.54, 3.22) | 0.920 | 70.00 |
treated
| Parameter | Estimate | 95% CI | p | age level |
|---|---|---|---|---|
| Indirect Effect (ACME) | -0.04 | (-0.09, 8.21e-03) | 0.120 | 20.00 |
| Direct Effect (ADE) | -0.04 | (-0.18, 0.08) | 0.560 | 20.00 |
| Prop. Mediated | 0.29 | (-3.55, 1.88) | 0.320 | 20.00 |
| ACME | 0.02 | (-0.05, 0.11) | 0.600 | 70.00 |
| ADE | -0.08 | (-0.34, 0.17) | 0.680 | 70.00 |
| Prop. Mediated | 0.04 | (-2.04, 4.03) | 0.920 | 70.00 |
average
| Parameter | Estimate | 95% CI | p | age level |
|---|---|---|---|---|
| Total Effect | -0.08 | (-0.23, 0.06) | 0.360 | 20.00 |
| Total Effect | -0.06 | (-0.38, 0.22) | 0.800 | 70.00 |
Total Effect
sessionInfo()
#> R version 4.2.0 (2022-04-22)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Debian GNU/Linux 11 (bullseye)
#>
#> Matrix products: default
#> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.13.so
#>
#> locale:
#> [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8
#> [5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8
#> [7] LC_PAPER=en_GB.UTF-8 LC_NAME=C
#> [9] LC_ADDRESS=C LC_TELEPHONE=C
#> [11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] parameters_0.18.1 mediation_4.5.0 sandwich_3.0-1 mvtnorm_1.1-3
#> [5] Matrix_1.4-1 MASS_7.3-57
#>
#> loaded via a namespace (and not attached):
#> [1] splines_4.2.0 R.utils_2.11.0 datawizard_0.4.1
#> [4] Formula_1.2-4 assertthat_0.2.1 latticeExtra_0.6-29
#> [7] yaml_2.3.5 bayestestR_0.12.1 pillar_1.7.0
#> [10] backports_1.4.1 lattice_0.20-45 glue_1.6.2
#> [13] digest_0.6.29 RColorBrewer_1.1-3 checkmate_2.1.0
#> [16] minqa_1.2.4 colorspace_2.0-3 htmltools_0.5.2
#> [19] R.oo_1.24.0 lpSolve_5.6.15 pkgconfig_2.0.3
#> [22] xtable_1.8-4 purrr_0.3.4 scales_1.2.0
#> [25] jpeg_0.1-9 lme4_1.1-29 emmeans_1.7.4-1
#> [28] tibble_3.1.7 htmlTable_2.4.0 styler_1.7.0
#> [31] generics_0.1.2 ggplot2_3.3.6 ellipsis_0.3.2
#> [34] TH.data_1.1-1 withr_2.5.0 nnet_7.3-17
#> [37] cli_3.3.0 survival_3.3-1 magrittr_2.0.3
#> [40] crayon_1.5.1 estimability_1.3 evaluate_0.15
#> [43] R.methodsS3_1.8.1 fs_1.5.2 fansi_1.0.3
#> [46] R.cache_0.15.0 nlme_3.1-157 foreign_0.8-82
#> [49] tools_4.2.0 data.table_1.14.2 multcomp_1.4-19
#> [52] lifecycle_1.0.1 stringr_1.4.0 munsell_0.5.0
#> [55] reprex_2.0.1 cluster_2.1.3 compiler_4.2.0
#> [58] rlang_1.0.2 grid_4.2.0 nloptr_2.0.3
#> [61] rstudioapi_0.13 htmlwidgets_1.5.4 base64enc_0.1-3
#> [64] rmarkdown_2.14 boot_1.3-28 codetools_0.2-18
#> [67] gtable_0.3.0 DBI_1.1.2 R6_2.5.1
#> [70] gridExtra_2.3 zoo_1.8-10 knitr_1.39
#> [73] dplyr_1.0.9 fastmap_1.1.0 utf8_1.2.2
#> [76] Hmisc_4.7-0 insight_0.17.1 stringi_1.7.6
#> [79] Rcpp_1.0.8.3 vctrs_0.4.1 rpart_4.1.16
#> [82] png_0.1-7 coda_0.19-4 tidyselect_1.1.2
#> [85] xfun_0.31
Created on 2022-06-02 by the reprex package (v2.0.1)
A question on pretty_names. I see they can be used for the model_parameters of certain objects/classes, like regressions, while cannot be used with the model_parameters of others, like htest.
Indeed, I see that
model <- t.test(iris$Sepal.Width, iris$Sepal.Length)
mmp <- model_parameters(model)
attr(mmp, "pretty_names") <- "mpg"
mmp |> print_md()
Error in `$<-.data.frame`(`*tmp*`, "Parameter", value = character(0)) :
replacement has 0 rows, data has 1
as the model_parameters output does not include Parameter, however
model <- t.test(mtcars$mpg ~ mtcars$vs)
mmp <- model_parameters(model)
attr(mmp, "pretty_names") <- "mpg"
mmp |> print_md()
Table: Welch Two Sample t-test
|Parameter | Group | mtcars$vs = 0 | mtcars$vs = 1 | Difference | 95% CI | t(22.72) | p |
|:----------|:---------:|:-------------:|:-------------:|:----------:|:---------------:|:--------:|:------:|
|mtcars$mpg | mtcars$vs | 16.62 | 24.56 | -7.94 | (-11.46, -4.42) | -4.67 | < .001 |
has no effect.
Then, my question is if is it some place where it is specified for which models pretty_names is used.