EXT01

Study Drug Exposure Table

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# When summary table contains only categorical or only numeric parameters

split_fun <- drop_split_levels

lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM") %>%
  split_rows_by("PARCAT2", split_label = "\nParameter Category (Drug A/Drug B)", label_pos = "topleft") %>%
  split_rows_by("PARAM", split_fun = split_fun) %>%
  analyze_vars(vars = "AVAL")

result <- build_table(lyt = lyt, df = adex, alt_counts_df = adsl)

result

                                                 A: Drug X        B: Placebo      C: Combination 
Parameter Category (Drug A/Drug B)                (N=134)           (N=134)           (N=132)    
—————————————————————————————————————————————————————————————————————————————————————————————————
Drug A                                                                                           
  Overall duration (days)                                                                        
    n                                               75                67                75       
    Mean (SD)                                   74.3 (41.6)       79.0 (43.1)       74.2 (39.5)  
    Median                                         77.0              80.0              78.0      
    Min - Max                                   5.0 - 149.0       2.0 - 150.0       1.0 - 147.0  
  Total dose administered                                                                        
    n                                               75                67                75       
    Mean (SD)                                 6675.2 (1110.9)   6505.1 (1249.3)   6982.4 (1272.5)
    Median                                        6720.0            6480.0            7200.0     
    Min - Max                                 4800.0 - 9360.0   4080.0 - 9360.0   4320.0 - 9360.0
  Total number of doses administered                                                             
    n                                               75                67                75       
    Mean (SD)                                    7.0 (0.0)         7.0 (0.0)         7.0 (0.0)   
    Median                                          7.0               7.0               7.0      
    Min - Max                                    7.0 - 7.0         7.0 - 7.0         7.0 - 7.0   
  Total number of missed doses during study                                                      
    n                                               75                67                75       
    Mean (SD)                                   10.5 (5.9)        10.0 (6.1)         9.5 (5.5)   
    Median                                         10.0              11.0               9.0      
    Min - Max                                   0.0 - 20.0        0.0 - 19.0        0.0 - 20.0   
Drug B                                                                                           
  Overall duration (days)                                                                        
    n                                               59                67                57       
    Mean (SD)                                   77.5 (40.5)       76.3 (41.0)       69.5 (46.2)  
    Median                                         79.0              76.0              65.0      
    Min - Max                                   2.0 - 149.0       5.0 - 148.0       1.0 - 149.0  
  Total dose administered                                                                        
    n                                               59                67                57       
    Mean (SD)                                 6630.5 (1334.0)   6297.3 (1291.1)   6505.3 (1080.7)
    Median                                        6720.0            6240.0            6480.0     
    Min - Max                                 4320.0 - 8880.0   4080.0 - 9120.0   4320.0 - 8640.0
  Total number of doses administered                                                             
    n                                               59                67                57       
    Mean (SD)                                    7.0 (0.0)         7.0 (0.0)         7.0 (0.0)   
    Median                                          7.0               7.0               7.0      
    Min - Max                                    7.0 - 7.0         7.0 - 7.0         7.0 - 7.0   
  Total number of missed doses during study                                                      
    n                                               59                67                57       
    Mean (SD)                                    9.1 (6.5)        10.0 (6.3)        10.7 (5.8)   
    Median                                          9.0              10.0              11.0      
    Min - Max                                   0.0 - 20.0        0.0 - 20.0        1.0 - 20.0

Experimental use!

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Code

# When summary table contains both categorical and numeric parameters,
# developer needs to do pre-processing to transform dataset to wide format.
adex_avalc_wide <- adex %>%
  filter(PARAMCD == "TDURD") %>%
  select(STUDYID, USUBJID, PARAMCD, AVALC, PARCAT2) %>%
  tidyr::pivot_wider(
    id_cols = c(STUDYID, USUBJID, PARCAT2),
    names_from = PARAMCD,
    values_from = AVALC
  ) %>%
  mutate(
    TDURDC = factor(TDURD, levels = c("0 - 30", "31 - 60", "61 - 90", ">= 91"))
  ) %>%
  select(-TDURD)

anl <- adex %>%
  select(STUDYID, USUBJID, ACTARM, PARAMCD, AVAL, PARCAT2) %>%
  tidyr::pivot_wider(
    id_cols = c(STUDYID, USUBJID, ACTARM, PARCAT2),
    names_from = PARAMCD,
    values_from = AVAL
  ) %>%
  left_join(adex_avalc_wide, by = c("STUDYID", "USUBJID", "PARCAT2")) %>%
  var_relabel(
    TDOSE = "Total dose administered",
    TNDOSE = "Total number of doses administered",
    TDURD = "Overall duration (days)",
    TNDOSMIS = "Total number of missed doses during study",
    TDURDC = "Overall duration (days)"
  )

lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM") %>%
  split_rows_by("PARCAT2", split_label = "\nParameter Category (Drug A/Drug B)", label_pos = "topleft") %>%
  analyze_vars(
    vars = c("TDURD", "TDURDC", "TDOSE", "TNDOSE"),
    var_labels = var_labels(anl)[c("TDURD", "TDURDC", "TDOSE", "TNDOSE")]
  )

result <- build_table(lyt = lyt, df = anl, alt_counts_df = adsl)

result

                                          A: Drug X        B: Placebo      C: Combination 
Parameter Category (Drug A/Drug B)         (N=134)           (N=134)           (N=132)    
——————————————————————————————————————————————————————————————————————————————————————————
Drug A                                                                                    
  Overall duration (days)                                                                 
    n                                        75                67                75       
    Mean (SD)                            74.3 (41.6)       79.0 (43.1)       74.2 (39.5)  
    Median                                  77.0              80.0              78.0      
    Min - Max                            5.0 - 149.0       2.0 - 150.0       1.0 - 147.0  
  Overall duration (days)                                                                 
    n                                        75                67                75       
    0 - 30                                12 (16%)         12 (17.9%)         15 (20%)    
    31 - 60                               18 (24%)         12 (17.9%)        14 (18.7%)   
    61 - 90                              19 (25.3%)        15 (22.4%)         18 (24%)    
    >= 91                                26 (34.7%)        28 (41.8%)        28 (37.3%)   
  Total dose administered                                                                 
    n                                        75                67                75       
    Mean (SD)                          6675.2 (1110.9)   6505.1 (1249.3)   6982.4 (1272.5)
    Median                                 6720.0            6480.0            7200.0     
    Min - Max                          4800.0 - 9360.0   4080.0 - 9360.0   4320.0 - 9360.0
  Total number of doses administered                                                      
    n                                        75                67                75       
    Mean (SD)                             7.0 (0.0)         7.0 (0.0)         7.0 (0.0)   
    Median                                   7.0               7.0               7.0      
    Min - Max                             7.0 - 7.0         7.0 - 7.0         7.0 - 7.0   
Drug B                                                                                    
  Overall duration (days)                                                                 
    n                                        59                67                57       
    Mean (SD)                            77.5 (40.5)       76.3 (41.0)       69.5 (46.2)  
    Median                                  79.0              76.0              65.0      
    Min - Max                            2.0 - 149.0       5.0 - 148.0       1.0 - 149.0  
  Overall duration (days)                                                                 
    n                                        59                67                57       
    0 - 30                                8 (13.6%)        10 (14.9%)        16 (28.1%)   
    31 - 60                              14 (23.7%)        16 (23.9%)        12 (21.1%)   
    61 - 90                              15 (25.4%)        17 (25.4%)        11 (19.3%)   
    >= 91                                22 (37.3%)        24 (35.8%)        18 (31.6%)   
  Total dose administered                                                                 
    n                                        59                67                57       
    Mean (SD)                          6630.5 (1334.0)   6297.3 (1291.1)   6505.3 (1080.7)
    Median                                 6720.0            6240.0            6480.0     
    Min - Max                          4320.0 - 8880.0   4080.0 - 9120.0   4320.0 - 8640.0
  Total number of doses administered                                                      
    n                                        59                67                57       
    Mean (SD)                             7.0 (0.0)         7.0 (0.0)         7.0 (0.0)   
    Median                                   7.0               7.0               7.0      
    Min - Max                             7.0 - 7.0         7.0 - 7.0         7.0 - 7.0

Experimental use!

WebR is a tool allowing you to run R code in the web browser. Modify the code below and click run to see the results. Alternatively, copy the code and click here to open WebR in a new tab.

Preview
Try this using WebR

Code

# When summary table contains both categorical and numeric parameters,
# developer needs to do pre-processing to transform dataset to wide format.
adex_avalc_wide <- adex %>%
  filter(PARAMCD == "TDURD") %>%
  select(STUDYID, USUBJID, PARAMCD, AVALC, PARCAT2) %>%
  tidyr::pivot_wider(
    id_cols = c(STUDYID, USUBJID, PARCAT2),
    names_from = PARAMCD,
    values_from = AVALC
  ) %>%
  mutate(
    TDURDC = factor(TDURD, levels = c("0 - 30", "31 - 60", "61 - 90", ">= 91"))
  ) %>%
  select(-TDURD)

anl <- adex %>%
  select(STUDYID, USUBJID, ACTARM, PARAMCD, AVAL, PARCAT2) %>%
  tidyr::pivot_wider(
    id_cols = c(STUDYID, USUBJID, ACTARM, PARCAT2),
    names_from = PARAMCD,
    values_from = AVAL
  ) %>%
  left_join(adex_avalc_wide, by = c("STUDYID", "USUBJID", "PARCAT2")) %>%
  var_relabel(
    TDOSE = "Total dose administered",
    TNDOSE = "Total number of doses administered",
    TDURD = "Overall duration (days)",
    TNDOSMIS = "Total number of missed doses during study",
    TDURDC = "Overall duration (days)"
  )

lyt <- basic_table(show_colcounts = TRUE) %>%
  split_cols_by("ACTARM") %>%
  split_rows_by("PARCAT2", split_label = "\nParameter Category (Drug A/Drug B)", label_pos = "topleft") %>%
  analyze_vars(
    vars = c("TDURD", "TDURDC", "TDOSE", "TNDOSE"),
    var_labels = var_labels(anl)[c("TDURD", "TDURDC", "TDOSE", "TNDOSE")]
  ) %>%
  count_missed_doses(
    "TNDOSMIS",
    thresholds = c(1, 5, 10, 15),
    var_labels = "Missed Doses"
  )

result <- build_table(lyt = lyt, df = anl, alt_counts_df = adsl)

result

                                          A: Drug X        B: Placebo      C: Combination 
Parameter Category (Drug A/Drug B)         (N=134)           (N=134)           (N=132)    
——————————————————————————————————————————————————————————————————————————————————————————
Drug A                                                                                    
  Overall duration (days)                                                                 
    n                                        75                67                75       
    Mean (SD)                            74.3 (41.6)       79.0 (43.1)       74.2 (39.5)  
    Median                                  77.0              80.0              78.0      
    Min - Max                            5.0 - 149.0       2.0 - 150.0       1.0 - 147.0  
  Overall duration (days)                                                                 
    n                                        75                67                75       
    0 - 30                                12 (16%)         12 (17.9%)         15 (20%)    
    31 - 60                               18 (24%)         12 (17.9%)        14 (18.7%)   
    61 - 90                              19 (25.3%)        15 (22.4%)         18 (24%)    
    >= 91                                26 (34.7%)        28 (41.8%)        28 (37.3%)   
  Total dose administered                                                                 
    n                                        75                67                75       
    Mean (SD)                          6675.2 (1110.9)   6505.1 (1249.3)   6982.4 (1272.5)
    Median                                 6720.0            6480.0            7200.0     
    Min - Max                          4800.0 - 9360.0   4080.0 - 9360.0   4320.0 - 9360.0
  Total number of doses administered                                                      
    n                                        75                67                75       
    Mean (SD)                             7.0 (0.0)         7.0 (0.0)         7.0 (0.0)   
    Median                                   7.0               7.0               7.0      
    Min - Max                             7.0 - 7.0         7.0 - 7.0         7.0 - 7.0   
  Missed Doses                                                                            
    n                                        75                67                75       
    At least 1 missed dose               74 (55.2%)         63 (47%)         73 (55.3%)   
    At least 5 missed doses               59 (44%)         49 (36.6%)        59 (44.7%)   
    At least 10 missed doses             41 (30.6%)        38 (28.4%)         37 (28%)    
    At least 15 missed doses             26 (19.4%)        21 (15.7%)        16 (12.1%)   
Drug B                                                                                    
  Overall duration (days)                                                                 
    n                                        59                67                57       
    Mean (SD)                            77.5 (40.5)       76.3 (41.0)       69.5 (46.2)  
    Median                                  79.0              76.0              65.0      
    Min - Max                            2.0 - 149.0       5.0 - 148.0       1.0 - 149.0  
  Overall duration (days)                                                                 
    n                                        59                67                57       
    0 - 30                                8 (13.6%)        10 (14.9%)        16 (28.1%)   
    31 - 60                              14 (23.7%)        16 (23.9%)        12 (21.1%)   
    61 - 90                              15 (25.4%)        17 (25.4%)        11 (19.3%)   
    >= 91                                22 (37.3%)        24 (35.8%)        18 (31.6%)   
  Total dose administered                                                                 
    n                                        59                67                57       
    Mean (SD)                          6630.5 (1334.0)   6297.3 (1291.1)   6505.3 (1080.7)
    Median                                 6720.0            6240.0            6480.0     
    Min - Max                          4320.0 - 8880.0   4080.0 - 9120.0   4320.0 - 8640.0
  Total number of doses administered                                                      
    n                                        59                67                57       
    Mean (SD)                             7.0 (0.0)         7.0 (0.0)         7.0 (0.0)   
    Median                                   7.0               7.0               7.0      
    Min - Max                             7.0 - 7.0         7.0 - 7.0         7.0 - 7.0   
  Missed Doses                                                                            
    n                                        59                67                57       
    At least 1 missed dose               56 (41.8%)         63 (47%)         57 (43.2%)   
    At least 5 missed doses              41 (30.6%)        50 (37.3%)        47 (35.6%)   
    At least 10 missed doses             27 (20.1%)        36 (26.9%)        31 (23.5%)   
    At least 15 missed doses             17 (12.7%)        18 (13.4%)        20 (15.2%)

Experimental use!

WebR is a tool allowing you to run R code in the web browser. Modify the code below and click run to see the results. Alternatively, copy the code and click here to open WebR in a new tab.

Code

library(tern)
library(dplyr)
library(tidyr)

adsl <- random.cdisc.data::cadsl
adex <- random.cdisc.data::cadex

# Ensure character variables are converted to factors and empty strings and NAs are explicit missing levels.
adsl <- df_explicit_na(adsl)
adex <- df_explicit_na(adex)

adex <- adex %>%
  filter(PARCAT1 == "OVERALL") %>%
  select(STUDYID, USUBJID, ACTARM, PARAMCD, PARAM, AVAL, PARCAT2) %>%
  mutate(
    PARAMCD = as.character(PARAMCD),
    AVALC = ""
  ) %>%
  droplevels()

# Add new param tdurd for treatment duration.
set.seed(99)
tdurd_adsl <- adsl %>%
  select(STUDYID, USUBJID, ACTARM) %>%
  mutate(
    PARAMCD = "TDURD",
    PARAM = "Overall duration (days)",
    AVAL = sample(1:150, size = nrow(adsl), replace = TRUE),
    AVALC = case_when(
      0 <= AVAL & AVAL <= 30 ~ "0 - 30",
      31 <= AVAL & AVAL <= 60 ~ "31 - 60",
      61 <= AVAL & AVAL <= 90 ~ "61 - 90",
      TRUE ~ ">= 91"
    )
  )
tdurd <- adex %>%
  filter(PARAMCD == "TNDOSE") %>%
  select(STUDYID, USUBJID, PARCAT2) %>%
  left_join(tdurd_adsl, by = c("STUDYID", "USUBJID"))

# Add new param tndosmis for missed doses.
tndosmis_adsl <- adsl %>%
  select(STUDYID, USUBJID, ACTARM) %>%
  mutate(
    PARAMCD = "TNDOSMIS",
    PARAM = "Total number of missed doses during study",
    AVAL = sample(0:20, size = nrow(adsl), replace = TRUE),
    AVALC = ""
  )
tndosmis <- adex %>%
  filter(PARAMCD == "TNDOSE") %>%
  select(STUDYID, USUBJID, PARCAT2) %>%
  left_join(tndosmis_adsl, by = c("STUDYID", "USUBJID"))

adex <- dplyr::bind_rows(adex, tdurd, tndosmis) %>%
  mutate(PARAM = factor(
    PARAM,
    levels = c(
      "Overall duration (days)", "Total dose administered", "Total number of doses administered",
      "Total number of missed doses during study"
    )
  ))

Code

library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  library(dplyr)

  ADSL <- random.cdisc.data::cadsl
  ADEX <- random.cdisc.data::cadex
  adex_labels <- unname(col_labels(ADEX))
  ADEX <- ADEX %>%
    filter(PARCAT1 == "OVERALL") %>%
    mutate(
      AVALCAT1 = case_when(
        PARAMCD == "TDOSE" & AVAL < 5000 ~ "LOW",
        PARAMCD == "TDOSE" & AVAL >= 5000 ~ "HIGH",
        PARAMCD == "TNDOSE" & AVAL < 10 ~ "< 10",
        PARAMCD == "TNDOSE" & AVAL >= 10 ~ ">= 10"
      )
    )
  col_labels(ADEX) <- c(adex_labels, "")
})
datanames <- c("ADSL", "ADEX")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADEX <- data[["ADEX"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_summary_by(
      label = "Exposure Table",
      dataname = "ADEX",
      arm_var = choices_selected(
        choices = variable_choices(ADEX, c("ARM", "ARMCD")),
        selected = "ARM"
      ),
      by_vars = choices_selected(
        choices = variable_choices(ADEX, c("PARCAT2", "PARAM")),
        selected = c("PARCAT2", "PARAM")
      ),
      summarize_vars = choices_selected(
        choices = variable_choices(ADEX, c("AVAL", "AVALCAT1")),
        selected = c("AVAL", "AVALCAT1")
      ),
      paramcd = choices_selected(
        choices = value_choices(ADEX, "PARAMCD", "PARAM"),
        selected = c("TDOSE", "TNDOSE")
      ),
      denominator = choices_selected(
        choices = c("n", "N", "omit"),
        selected = "N"
      )
    )
  ), # Set initial filter state as single study drug to produce smaller table
  filter = teal_slices(
    teal_slice("ADEX", "PARCAT2", selected = "Drug A"),
    teal_slice("ADEX", "AVAL", selected = NULL)
  )
)

shinyApp(app$ui, app$server)

Warning: The 'plotly_relayout' event tied a source ID of
'teal-main_ui-filter_panel-active-ADEX-filter-ADEX_AVAL-inputs-histogram_plot'
is not registered. In order to obtain this event data, please add
`event_register(p, 'plotly_relayout')` to the plot (`p`) that you wish to
obtain event data from.

Experimental use!

shinylive allow you to modify to run shiny application entirely in the web browser. Modify the code below and click re-run the app to see the results. The performance is slighly worse and some of the features (e.g. downloading) might not work at all.

#| standalone: true
#| viewerHeight: 800
#| editorHeight: 200
#| components: [viewer, editor]
#| layout: vertical

# -- WEBR HELPERS --
options(webr_pkg_repos = c("r-universe" = "https://insightsengineering.r-universe.dev", getOption("webr_pkg_repos")))

# -- APP CODE --
library(teal.modules.clinical)

## Data reproducible code
data <- teal_data()
data <- within(data, {
  library(dplyr)

  ADSL <- random.cdisc.data::cadsl
  ADEX <- random.cdisc.data::cadex
  adex_labels <- unname(col_labels(ADEX))
  ADEX <- ADEX %>%
    filter(PARCAT1 == "OVERALL") %>%
    mutate(
      AVALCAT1 = case_when(
        PARAMCD == "TDOSE" & AVAL < 5000 ~ "LOW",
        PARAMCD == "TDOSE" & AVAL >= 5000 ~ "HIGH",
        PARAMCD == "TNDOSE" & AVAL < 10 ~ "< 10",
        PARAMCD == "TNDOSE" & AVAL >= 10 ~ ">= 10"
      )
    )
  col_labels(ADEX) <- c(adex_labels, "")
})
datanames <- c("ADSL", "ADEX")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADEX <- data[["ADEX"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_t_summary_by(
      label = "Exposure Table",
      dataname = "ADEX",
      arm_var = choices_selected(
        choices = variable_choices(ADEX, c("ARM", "ARMCD")),
        selected = "ARM"
      ),
      by_vars = choices_selected(
        choices = variable_choices(ADEX, c("PARCAT2", "PARAM")),
        selected = c("PARCAT2", "PARAM")
      ),
      summarize_vars = choices_selected(
        choices = variable_choices(ADEX, c("AVAL", "AVALCAT1")),
        selected = c("AVAL", "AVALCAT1")
      ),
      paramcd = choices_selected(
        choices = value_choices(ADEX, "PARAMCD", "PARAM"),
        selected = c("TDOSE", "TNDOSE")
      ),
      denominator = choices_selected(
        choices = c("n", "N", "omit"),
        selected = "N"
      )
    )
  ), # Set initial filter state as single study drug to produce smaller table
  filter = teal_slices(
    teal_slice("ADEX", "PARCAT2", selected = "Drug A"),
    teal_slice("ADEX", "AVAL", selected = NULL)
  )
)

shinyApp(app$ui, app$server)

Reproducibility

Timestamp

[1] "2024-11-02 18:32:12 UTC"

Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.4.1 (2024-06-14)
 os       Ubuntu 22.04.5 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2024-11-02
 pandoc   3.4 @ /usr/bin/ (via rmarkdown)

─ Packages ───────────────────────────────────────────────────────────────────
 package               * version  date (UTC) lib source
 backports               1.5.0    2024-05-23 [1] CRAN (R 4.4.1)
 brio                    1.1.5    2024-04-24 [1] CRAN (R 4.4.1)
 broom                   1.0.7    2024-09-26 [1] CRAN (R 4.4.1)
 bslib                   0.8.0    2024-07-29 [1] CRAN (R 4.4.1)
 cachem                  1.1.0    2024-05-16 [1] CRAN (R 4.4.1)
 callr                   3.7.6    2024-03-25 [1] CRAN (R 4.4.1)
 checkmate               2.3.2    2024-07-29 [1] CRAN (R 4.4.1)
 chromote                0.3.1    2024-08-30 [1] CRAN (R 4.4.1)
 cli                     3.6.3    2024-06-21 [1] CRAN (R 4.4.1)
 coda                    0.19-4.1 2024-01-31 [1] CRAN (R 4.4.1)
 codetools               0.2-20   2024-03-31 [2] CRAN (R 4.4.1)
 colorspace              2.1-1    2024-07-26 [1] CRAN (R 4.4.1)
 data.table              1.16.2   2024-10-10 [1] CRAN (R 4.4.1)
 digest                  0.6.37   2024-08-19 [1] CRAN (R 4.4.1)
 dplyr                 * 1.1.4    2023-11-17 [1] CRAN (R 4.4.1)
 emmeans                 1.10.5   2024-10-14 [1] CRAN (R 4.4.1)
 estimability            1.5.1    2024-05-12 [1] CRAN (R 4.4.1)
 evaluate                1.0.1    2024-10-10 [1] CRAN (R 4.4.1)
 fansi                   1.0.6    2023-12-08 [1] CRAN (R 4.4.1)
 fastmap                 1.2.0    2024-05-15 [1] CRAN (R 4.4.1)
 fontawesome             0.5.2    2023-08-19 [1] CRAN (R 4.4.1)
 forcats                 1.0.0    2023-01-29 [1] CRAN (R 4.4.1)
 formatR                 1.14     2023-01-17 [1] CRAN (R 4.4.1)
 formatters            * 0.5.9    2024-09-12 [1] CRAN (R 4.4.1)
 geepack                 1.3.12   2024-09-23 [1] CRAN (R 4.4.1)
 generics                0.1.3    2022-07-05 [1] CRAN (R 4.4.1)
 ggplot2                 3.5.1    2024-04-23 [1] CRAN (R 4.4.1)
 glue                    1.8.0    2024-09-30 [1] CRAN (R 4.4.1)
 gtable                  0.3.6    2024-10-25 [1] CRAN (R 4.4.1)
 htmltools               0.5.8.1  2024-04-04 [1] CRAN (R 4.4.1)
 htmlwidgets             1.6.4    2023-12-06 [1] CRAN (R 4.4.1)
 httpuv                  1.6.15   2024-03-26 [1] CRAN (R 4.4.1)
 httr                    1.4.7    2023-08-15 [1] CRAN (R 4.4.1)
 jquerylib               0.1.4    2021-04-26 [1] CRAN (R 4.4.1)
 jsonlite                1.8.9    2024-09-20 [1] CRAN (R 4.4.1)
 knitr                   1.48     2024-07-07 [1] CRAN (R 4.4.1)
 later                   1.3.2    2023-12-06 [1] CRAN (R 4.4.1)
 lattice                 0.22-6   2024-03-20 [2] CRAN (R 4.4.1)
 lazyeval                0.2.2    2019-03-15 [1] CRAN (R 4.4.1)
 lifecycle               1.0.4    2023-11-07 [1] CRAN (R 4.4.1)
 logger                  0.4.0    2024-10-22 [1] CRAN (R 4.4.1)
 magrittr              * 2.0.3    2022-03-30 [1] CRAN (R 4.4.1)
 MASS                    7.3-61   2024-06-13 [2] CRAN (R 4.4.1)
 Matrix                  1.7-0    2024-04-26 [1] CRAN (R 4.4.1)
 memoise                 2.0.1    2021-11-26 [1] CRAN (R 4.4.1)
 mime                    0.12     2021-09-28 [1] CRAN (R 4.4.1)
 multcomp                1.4-26   2024-07-18 [1] CRAN (R 4.4.1)
 munsell                 0.5.1    2024-04-01 [1] CRAN (R 4.4.1)
 mvtnorm                 1.3-1    2024-09-03 [1] CRAN (R 4.4.1)
 nlme                    3.1-166  2024-08-14 [2] CRAN (R 4.4.1)
 pillar                  1.9.0    2023-03-22 [1] CRAN (R 4.4.1)
 pkgconfig               2.0.3    2019-09-22 [1] CRAN (R 4.4.1)
 plotly                  4.10.4   2024-01-13 [1] CRAN (R 4.4.1)
 processx                3.8.4    2024-03-16 [1] CRAN (R 4.4.1)
 promises                1.3.0    2024-04-05 [1] CRAN (R 4.4.1)
 ps                      1.8.1    2024-10-28 [1] CRAN (R 4.4.1)
 purrr                   1.0.2    2023-08-10 [1] CRAN (R 4.4.1)
 R6                      2.5.1    2021-08-19 [1] CRAN (R 4.4.1)
 random.cdisc.data       0.3.16   2024-11-02 [1] https://insightsengineering.r-universe.dev (R 4.4.1)
 rbibutils               2.3      2024-10-04 [1] CRAN (R 4.4.1)
 Rcpp                    1.0.13   2024-07-17 [1] CRAN (R 4.4.1)
 Rdpack                  2.6.1    2024-08-06 [1] CRAN (R 4.4.1)
 rlang                   1.1.4    2024-06-04 [1] CRAN (R 4.4.1)
 rmarkdown               2.28     2024-08-17 [1] CRAN (R 4.4.1)
 rtables               * 0.6.10   2024-09-20 [1] CRAN (R 4.4.1)
 sandwich                3.1-1    2024-09-15 [1] CRAN (R 4.4.1)
 sass                    0.4.9    2024-03-15 [1] CRAN (R 4.4.1)
 scales                  1.3.0    2023-11-28 [1] CRAN (R 4.4.1)
 sessioninfo             1.2.2    2021-12-06 [1] CRAN (R 4.4.1)
 shiny                 * 1.9.1    2024-08-01 [1] CRAN (R 4.4.1)
 shinycssloaders         1.1.0    2024-07-30 [1] CRAN (R 4.4.1)
 shinyjs                 2.1.0    2021-12-23 [1] CRAN (R 4.4.1)
 shinyvalidate           0.1.3    2023-10-04 [1] CRAN (R 4.4.1)
 shinyWidgets            0.8.7    2024-09-23 [1] CRAN (R 4.4.1)
 stringi                 1.8.4    2024-05-06 [1] CRAN (R 4.4.1)
 stringr                 1.5.1    2023-11-14 [1] CRAN (R 4.4.1)
 survival                3.7-0    2024-06-05 [2] CRAN (R 4.4.1)
 teal                  * 0.15.2   2024-03-07 [1] CRAN (R 4.4.1)
 teal.code             * 0.5.0    2024-01-11 [1] CRAN (R 4.4.1)
 teal.data             * 0.6.0    2024-04-30 [1] CRAN (R 4.4.1)
 teal.logger             0.3.0    2024-11-02 [1] https://insightsengineering.r-universe.dev (R 4.4.1)
 teal.modules.clinical * 0.9.1    2024-04-27 [1] CRAN (R 4.4.1)
 teal.reporter           0.3.1    2024-03-15 [1] CRAN (R 4.4.1)
 teal.slice            * 0.5.1    2024-04-30 [1] CRAN (R 4.4.1)
 teal.transform        * 0.5.0    2024-02-17 [1] CRAN (R 4.4.1)
 teal.widgets            0.4.2    2023-12-14 [1] CRAN (R 4.4.1)
 tern                  * 0.9.6    2024-09-24 [1] CRAN (R 4.4.1)
 tern.gee                0.1.5    2024-08-23 [1] CRAN (R 4.4.1)
 testthat                3.2.1.1  2024-04-14 [1] CRAN (R 4.4.1)
 TH.data                 1.1-2    2023-04-17 [1] CRAN (R 4.4.1)
 tibble                  3.2.1    2023-03-20 [1] CRAN (R 4.4.1)
 tidyr                 * 1.3.1    2024-01-24 [1] CRAN (R 4.4.1)
 tidyselect              1.2.1    2024-03-11 [1] CRAN (R 4.4.1)
 utf8                    1.2.4    2023-10-22 [1] CRAN (R 4.4.1)
 vctrs                   0.6.5    2023-12-01 [1] CRAN (R 4.4.1)
 viridisLite             0.4.2    2023-05-02 [1] CRAN (R 4.4.1)
 webshot                 0.5.5    2023-06-26 [1] CRAN (R 4.4.1)
 webshot2                0.1.1    2023-08-11 [1] CRAN (R 4.4.1)
 websocket               1.4.2    2024-07-22 [1] CRAN (R 4.4.1)
 withr                   3.0.2    2024-10-28 [1] CRAN (R 4.4.1)
 xfun                    0.49     2024-10-31 [1] CRAN (R 4.4.1)
 xtable                  1.8-4    2019-04-21 [1] CRAN (R 4.4.1)
 yaml                    2.3.10   2024-07-26 [1] CRAN (R 4.4.1)
 zoo                     1.8-12   2023-04-13 [1] CRAN (R 4.4.1)

 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library

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`.lock` file

Download the .lock file and use renv::restore() on it to recreate environment used to generate this website.

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teal App

Reproducibility

Timestamp

Session Info

.lock file

`teal` App

`.lock` file