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source("R/setup-script.R")5 Data and Environment Setup
5.1 Source Setup Script
In order to run the code included in this book, you first need to run “/R/setup-script.R” to install/load required packages and read the data. The data are located in “/data/preregistration_3_data_public.csv”.
5.2 Session Info
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R version 4.5.0 (2025-04-11)
Platform: aarch64-apple-darwin20
Running under: macOS Sonoma 14.6.1
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.1
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/New_York
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] lubridate_1.9.4 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4
[5] purrr_1.0.4 readr_2.1.5 tidyr_1.3.1 tibble_3.2.1
[9] tidyverse_2.0.0 ggpubr_0.6.0 rstatix_0.7.2 showtext_0.9-7
[13] showtextdb_3.0 sysfonts_0.8.9 patchwork_1.3.0 GGally_2.2.1
[17] ggplot2_3.5.2 sjtable2df_0.0.4 sjlabelled_1.2.0 sjmisc_2.8.10
[21] sjPlot_2.8.17 lmerTest_3.1-3 lme4_1.1-37 mediation_4.5.0
[25] sandwich_3.1-1 mvtnorm_1.3-3 Matrix_1.7-3 MASS_7.3-65
[29] gvlma_1.0.0.3 performance_0.15.1 kableExtra_1.4.0 pacman_0.5.1
loaded via a namespace (and not attached):
[1] Rdpack_2.6.4 gridExtra_2.3 rlang_1.1.6
[4] magrittr_2.0.3 compiler_4.5.0 systemfonts_1.2.2
[7] vctrs_0.6.5 crayon_1.5.3 pkgconfig_2.0.3
[10] fastmap_1.2.0 backports_1.5.0 rmarkdown_2.29
[13] tzdb_0.5.0 nloptr_2.2.1 bit_4.6.0
[16] xfun_0.52 jsonlite_2.0.0 ggeffects_2.2.1
[19] parallel_4.5.0 broom_1.0.8 cluster_2.1.8.1
[22] R6_2.6.1 stringi_1.8.7 RColorBrewer_1.1-3
[25] car_3.1-3 boot_1.3-31 rpart_4.1.24
[28] numDeriv_2016.8-1.1 Rcpp_1.0.14 knitr_1.50
[31] zoo_1.8-14 base64enc_0.1-3 splines_4.5.0
[34] nnet_7.3-20 timechange_0.3.0 tidyselect_1.2.1
[37] rstudioapi_0.17.1 abind_1.4-8 yaml_2.3.10
[40] codetools_0.2-20 curl_6.2.2 lattice_0.22-7
[43] plyr_1.8.9 withr_3.0.2 evaluate_1.0.3
[46] foreign_0.8-90 archive_1.1.12 ggstats_0.9.0
[49] xml2_1.3.8 lpSolve_5.6.23 pillar_1.10.2
[52] carData_3.0-5 checkmate_2.3.2 reformulas_0.4.0
[55] insight_1.4.2 generics_0.1.3 vroom_1.6.5
[58] hms_1.1.3 scales_1.4.0 minqa_1.2.8
[61] glue_1.8.0 Hmisc_5.2-3 tools_4.5.0
[64] data.table_1.17.8 ggsignif_0.6.4 grid_4.5.0
[67] rbibutils_2.3 datawizard_1.2.0 colorspace_2.1-1
[70] nlme_3.1-168 htmlTable_2.4.3 Formula_1.2-5
[73] cli_3.6.5 viridisLite_0.4.2 svglite_2.1.3
[76] sjstats_0.19.0 gtable_0.3.6 digest_0.6.37
[79] htmlwidgets_1.6.4 farver_2.1.2 htmltools_0.5.8.1
[82] lifecycle_1.0.4 bit64_4.6.0-1 5.3 Datasets
The analyses in the main text are run using two forms of the data, one for each research question / analysis type. Summaries of the data charactaristics are described below.
RQ1 Data
These data are in long format - (22 items x 149 participants - 3 NA values) x 3 judgments per item = 9825 observations.
Note
the variable perception is equivalent to “judgment” in the manuscript.
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data_rq1 |> glimpse()Rows: 9,825
Columns: 17
$ Participant <chr> "mvU3yT4uTFpW58Z0", "mvU3yT4uTFpW58Z0", "mvU3yT4…
$ Condition <fct> Control, Control, Control, Control, Control, Con…
$ Gender <fct> Men, Men, Men, Men, Men, Men, Men, Men, Men, Men…
$ Cohort <fct> Cohort 1, Cohort 1, Cohort 1, Cohort 1, Cohort 1…
$ Timepoint <fct> Baseline, Baseline, Baseline, Baseline, Baseline…
$ Semester_Week <dbl> 1.912752, 1.912752, 1.912752, 1.912752, 1.912752…
$ Test_Version <fct> B, B, B, B, B, B, B, B, B, B, B, B, B, B, B, B, …
$ Part <chr> "Quantitative", "Quantitative", "Quantitative", …
$ Question <dbl> 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, …
$ Item <chr> "B01", "B01", "B01", "B02", "B02", "B02", "B03",…
$ Score <dbl> 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, …
$ `Item-Level Accuracy` <fct> Incorrect, Incorrect, Incorrect, Incorrect, Inco…
$ Accuracy_Raw <dbl> 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, …
$ Baseline_Threat <dbl> 1.63132, 1.63132, 1.63132, 1.63132, 1.63132, 1.6…
$ EMA_Threat <dbl> 3.416667, 3.416667, 3.416667, 3.416667, 3.416667…
$ perception <fct> Confidence, Anxiety, Difficulty, Confidence, Anx…
$ rating <dbl> 1, 6, 6, 5, 6, 2, 4, 6, 3, 5, 6, 4, 5, 6, 4, 4, …Participant-Level Variables
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Participant Condition Gender Cohort
Length:149 Control :73 Men :66 Cohort 1:61
Class :character Mindfulness:76 Women or Non-binary:83 Cohort 2:16
Mode :character Cohort 3:72 Show/Hide Code
rq1_participants |>
get_summary_stats(show = c("min", "max", "mean", "sd"))| variable | n | min | max | mean | sd |
|---|---|---|---|---|---|
| Semester_Week | 149 | -4.087 | 4.913 | 0 | 2.790 |
| Baseline_Threat | 149 | -3.102 | 2.865 | 0 | 1.297 |
Item (Observation)-Level Variables
Note
Score includes values between 0 and 1 since 4 of the items (A01, B01, A10, and B10) were open-ended and could be awarded partial credit. Item-Level Accuracy (factor version) and Accuracy_Raw (numeric version) were derived from Score to compare incorrect responses to those that were at least partially correct (Score > 0).
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data_rq1 |>
select(
Item,
Timepoint,
Test_Version,
`Item-Level Accuracy`,
perception
) |>
summary() Item Timepoint Test_Version Item-Level Accuracy
Length:9825 Baseline:4470 A:4908 Incorrect:5547
Class :character Posttest:5355 B:4917 Correct :4278
Mode :character
perception
Confidence:3275
Anxiety :3275
Difficulty:3275 Show/Hide Code
data_rq1 |>
select(
Score,
Accuracy_Raw,
rating
) |>
get_summary_stats(show = c("min", "max", "mean", "sd"))| variable | n | min | max | mean | sd |
|---|---|---|---|---|---|
| Score | 9825 | 0 | 1 | 0.404 | 0.478 |
| Accuracy_Raw | 9825 | 0 | 1 | 0.435 | 0.496 |
| rating | 9825 | 1 | 6 | 3.474 | 1.408 |
RQ2 Data
Data are in wide format, so everything varies at the participant level. Judgment ratings and accuracy scores are averaged at baseline and posttest. Continuous variables are standardized and numeric dummy variables with contrast coding are created for Cohort because the mediation package does not accept factors with contrast coding, but this has no bearing on the results. One participant’s data was removed because they did not complete any EMA surveys.
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data_rq2 |> glimpse()Rows: 148
Columns: 21
$ Participant <chr> "mvU3yT4uTFpW58Z0", "bTvjXPvFUSNyAt5t", "hx3UKKU…
$ Condition <fct> Control, Control, Control, Control, Control, Con…
$ Gender <fct> Men, Men, Men, Women or Non-binary, Men, Women o…
$ Cohort <fct> Cohort 1, Cohort 1, Cohort 1, Cohort 1, Cohort 3…
$ Semester_Week <dbl> 0.6786886, 0.6786886, 0.6786886, 1.0374240, -0.7…
$ Baseline_Threat <dbl> 1.25100904, -0.75116043, -1.05918650, 1.89273003…
$ EMA_Threat <dbl> 1.55096412, 1.29550795, -0.95250627, 1.29550795,…
$ Baseline_n_items <int> 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, …
$ Posttest_n_items <int> 12, 12, 12, 12, 12, 12, 11, 12, 12, 12, 12, 12, …
$ Baseline_Score <dbl> -0.31125932, 0.33654914, -0.49120612, -1.6068762…
$ Posttest_Score <dbl> -1.34709242, 1.43972775, -0.78972839, -2.4618204…
$ Baseline_Confidence <dbl> -0.37485943, 0.01220473, 0.39926888, -2.18115882…
$ Posttest_Confidence <dbl> 0.23891063, 0.53917812, 0.53917812, -3.36429935,…
$ Baseline_Anxiety <dbl> 2.49202355, -0.85159304, -0.57295832, 1.65611940…
$ Posttest_Anxiety <dbl> 2.15254688, -0.25189270, -0.99809809, 2.40128201…
$ Baseline_Difficulty <dbl> 1.15470752, -1.16207408, -0.20810518, 2.24495769…
$ Posttest_Difficulty <dbl> 1.4257825, -0.7405502, -0.0184393, 2.4573694, 0.…
$ Baseline_Test_Version <chr> "B", "A", "B", "A", "B", "A", "A", "B", "A", "A"…
$ Posttest_Test_Version <fct> A, B, A, B, A, B, B, A, B, B, A, B, B, B, B, B, …
$ Cohort_2 <dbl> -0.3469771, -0.3469771, -0.3469771, -0.3469771, …
$ Cohort_3 <dbl> -0.9569993, -0.9569993, -0.9569993, -0.9569993, …Show/Hide Code
Participant Condition Gender Cohort
Length:148 Control :73 Men :66 Cohort 1:61
Class :character Mindfulness:75 Women or Non-binary:82 Cohort 2:16
Mode :character Cohort 3:71
Baseline_Test_Version Posttest_Test_Version
A:75 A:73
B:73 B:75
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data_rq2 |>
get_summary_stats(show = c("min", "max", "mean", "sd"))| variable | n | min | max | mean | sd |
|---|---|---|---|---|---|
| Semester_Week | 148 | -1.474 | 1.755 | 0.00 | 1.000 |
| Baseline_Threat | 148 | -2.394 | 2.201 | 0.00 | 1.000 |
| EMA_Threat | 148 | -2.230 | 2.420 | 0.00 | 1.000 |
| Baseline_n_items | 148 | 10.000 | 10.000 | 10.00 | 0.000 |
| Posttest_n_items | 148 | 11.000 | 12.000 | 11.98 | 0.141 |
| Baseline_Score | 148 | -2.111 | 3.511 | 0.00 | 1.000 |
| Posttest_Score | 148 | -2.462 | 2.957 | 0.00 | 1.000 |
| Baseline_Confidence | 148 | -3.213 | 2.206 | 0.00 | 1.000 |
| Posttest_Confidence | 148 | -3.464 | 1.840 | 0.00 | 1.000 |
| Baseline_Anxiety | 148 | -2.152 | 2.492 | 0.00 | 1.000 |
| Posttest_Anxiety | 148 | -1.993 | 2.650 | 0.00 | 1.000 |
| Baseline_Difficulty | 148 | -2.389 | 2.381 | 0.00 | 1.000 |
| Posttest_Difficulty | 148 | -2.701 | 2.457 | 0.00 | 1.000 |
| Cohort_2 | 148 | -0.347 | 2.863 | 0.00 | 1.000 |
| Cohort_3 | 148 | -0.957 | 1.038 | 0.00 | 1.000 |