Empty plot in 4.3.5?

[inigourrestarazu]

Hi!

I am not able to reproduce the plot in section 4.3.5. I copy-pasted the code in the whole chapter, but the bars of the plot are missing. The problem is somehow related to the "df_recall_ext", because when I drop it from the pp_check function, I get the posterior predictive plot for the sizes in "df_recall".

I don't know if it's just my problem.

[bnicenboim]

I just tried it and it worked for me. I'm using bayesplot_1.9.0, are you using an older version perhaps?

can you past all the code that you run, the output of df_recall_ext, and the output of sessionInfo()?

[inigourrestarazu]

Hi, there!

The version I have for bayesplot is 1.10. Anyway, it may totally be my thing. I don't usually load the packages, but specify package::function and it may be related to that.

The code:

df_recall <- bcogsci::df_recall

df_recall <- df_recall %>% dplyr::mutate(
  c_set_size = set_size - mean(set_size)
)

fit_recall <-
  brms::brm(correct ~ 1 + c_set_size,
            data = df_recall,
            family = brms::bernoulli(link = "logit"),
            prior = c(
              brms::prior(normal(0, 1.5), class = Intercept),
              brms::prior(normal(0, 0.1), class = b, coef = c_set_size)
            ))

df_recall_ext <- df_recall %>%
  bind_rows(tibble(
    set_size = rep(c(3, 5, 7), 23),
    c_set_size = set_size -
      mean(df_recall$set_size),
    correct = 0
  ))
# nicer label for the facets:
set_size <- paste("set size", 2:8) %>%
  setNames(-3:3)
pp_check(fit_recall,
  type = "stat_grouped",
  stat = "mean",
  group = "c_set_size",
  newdata = df_recall_ext,
  facet_args = list(
    ncol = 1, scales = "fixed",
    labeller = as_labeller(set_size)
  ),
  binwidth = 0.02
)

Output of df_recall_ext

df_recall_ext
# A tibble: 161 × 8
   subj  set_size correct trial session block tested c_set_size
   <chr>    <dbl>   <dbl> <int>   <int> <int>  <int>      <dbl>
 1 10           4       1     1       1     1      2         -1
 2 10           8       0     4       1     1      8          3
 3 10           2       1     9       1     1      2         -3
 4 10           6       1    23       1     1      2          1
 5 10           4       1     5       1     2      3         -1
 6 10           8       0     7       1     2      5          3
 7 10           6       1    10       1     2      3          1
 8 10           2       1    19       1     2      1         -3
 9 10           2       1     9       1     3      2         -3
10 10           6       0    16       1     3      5          1
# … with 151 more rows
# ℹ Use `print(n = ...)` to see more rows

SessionInfo:

sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS 13.2.1

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets 
[6] methods   base     

other attached packages:
 [1] forcats_0.5.2      stringr_1.5.0     
 [3] dplyr_1.0.10       purrr_1.0.1       
 [5] readr_2.1.3        tidyr_1.3.0       
 [7] tibble_3.1.8       ggplot2_3.4.0     
 [9] tidyverse_1.3.2    brms_2.18.0       
[11] Rcpp_1.0.10        bcogsci_0.0.0.9000
[13] tidybayes_3.0.2   

loaded via a namespace (and not attached):
  [1] readxl_1.4.1         backports_1.4.1     
  [3] plyr_1.8.8           igraph_1.3.5        
  [5] splines_4.2.0        svUnit_1.0.6        
  [7] crosstalk_1.2.0      rstantools_2.2.0    
  [9] inline_0.3.19        digest_0.6.31       
 [11] htmltools_0.5.4      fansi_1.0.4         
 [13] magrittr_2.0.3       checkmate_2.1.0     
 [15] googlesheets4_1.0.1  tzdb_0.3.0          
 [17] modelr_0.1.10        RcppParallel_5.1.6  
 [19] matrixStats_0.63.0   xts_0.12.2          
 [21] timechange_0.1.1     prettyunits_1.1.1   
 [23] colorspace_2.1-0     rvest_1.0.3         
 [25] ggdist_3.2.0         haven_2.5.1         
 [27] rbibutils_2.2.13     xfun_0.35           
 [29] jsonlite_1.8.4       callr_3.7.3         
 [31] crayon_1.5.2         lme4_1.1-31         
 [33] zoo_1.8-11           glue_1.6.2          
 [35] gargle_1.2.1         gtable_0.3.1        
 [37] emmeans_1.8.3        sjstats_0.18.2      
 [39] sjmisc_2.8.9         distributional_0.3.1
 [41] pkgbuild_1.4.0       rstan_2.21.8        
 [43] abind_1.4-5          scales_1.2.1        
 [45] mvtnorm_1.1-3        DBI_1.1.3           
 [47] ggeffects_1.1.4      miniUI_0.1.1.1      
 [49] xtable_1.8-4         performance_0.10.1  
 [51] stats4_4.2.0         StanHeaders_2.21.0-7
 [53] DT_0.26              httr_1.4.4          
 [55] datawizard_0.6.4     htmlwidgets_1.5.4   
 [57] threejs_0.3.3        arrayhelpers_1.1-0  
 [59] posterior_1.3.1      ellipsis_0.3.2      
 [61] pkgconfig_2.0.3      loo_2.5.1           
 [63] farver_2.1.1         dbplyr_2.2.1        
 [65] utf8_1.2.2           tidyselect_1.2.0    
 [67] labeling_0.4.2       rlang_1.0.6         
 [69] reshape2_1.4.4       later_1.3.0         
 [71] munsell_0.5.0        cellranger_1.1.0    
 [73] tools_4.2.0          cli_3.6.0           
 [75] generics_0.1.3       sjlabelled_1.2.0    
 [77] broom_1.0.1          evaluate_0.18       
 [79] fastmap_1.1.0        yaml_2.3.6          
 [81] fs_1.5.2             processx_3.8.0      
 [83] knitr_1.41           nlme_3.1-160        
 [85] mime_0.12            xml2_1.3.3          
 [87] compiler_4.2.0       bayesplot_1.10.0    
 [89] shinythemes_1.2.0    rstudioapi_0.14     
 [91] reprex_2.0.2         stringi_1.7.8       
 [93] ps_1.7.2             Brobdingnag_1.2-9   
 [95] lattice_0.20-45      Matrix_1.5-3        
 [97] nloptr_2.0.3         markdown_1.4        
 [99] shinyjs_2.1.0        tensorA_0.36.2      
[101] vctrs_0.5.2          pillar_1.8.1        
[103] lifecycle_1.0.3      Rdpack_2.4          
[105] bridgesampling_1.1-2 estimability_1.4.1  
[107] insight_0.18.8       httpuv_1.6.6        
[109] extraDistr_1.9.1     R6_2.5.1            
[111] promises_1.2.0.1     gridExtra_2.3       
[113] codetools_0.2-18     boot_1.3-28.1       
[115] colourpicker_1.2.0   MASS_7.3-58.1       
[117] gtools_3.9.4         assertthat_0.2.1    
[119] withr_2.5.0          shinystan_2.6.0     
[121] hms_1.1.2            bayestestR_0.13.0   
[123] parallel_4.2.0       grid_4.2.0          
[125] sjPlot_2.8.12        coda_0.19-4         
[127] minqa_1.2.5          rmarkdown_2.18      
[129] googledrive_2.0.0    lubridate_1.9.0     
[131] shiny_1.7.3          base64enc_0.1-3     
[133] dygraphs_1.1.1.6    

The plot:

[bnicenboim]

I'm sorry I never came back to this. I can generate the plot with your code.