MNG01

Mean Plot

Output

Preview
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Code

plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  subtitle = "Laboratory Test:"
)
plot

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.

R Code

Start Over

Run Code

plot <- g_lineplot(

df = adlb_f,

alt_counts_df = adsl_f,

subtitle = "Laboratory Test:"

)

plot

_webr_editor_2 = Object {code: "plot <- g_lineplot(\n df = adlb_f,\n alt_counts_df = adsl_f,\n subtitle = \"Laboratory Test:\"\n)\nplot", options: Object, indicator: Ke}

Preview
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Code

plot <- g_lineplot(
  df = advs_f,
  alt_counts_df = adsl_f,
  variables = control_lineplot_vars(y = "CHG"),
  title = "Plot of Mean and 95% Confidence Intervals of Change from Baseline by Visit",
  subtitle = "Assessment:"
)
plot

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.

R Code

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Run Code

plot <- g_lineplot(

df = advs_f,

alt_counts_df = adsl_f,

variables = control_lineplot_vars(y = "CHG"),

title = "Plot of Mean and 95% Confidence Intervals of Change from Baseline by Visit",

subtitle = "Assessment:"

)

plot

_webr_editor_3 = Object {code: "plot <- g_lineplot(\n df = advs_f,\n alt_counts_df…line by Visit\",\n subtitle = \"Assessment:\"\n)\nplot", options: Object, indicator: Ke}

Preview
Try this using WebR

Code

plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  interval = "mean_sdi",
  whiskers = c("mean_sdi_lwr", "mean_sdi_upr"),
  title = "Plot of Mean (+/-SD)",
  subtitle = "Laboratory Test:"
)
plot

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.

R Code

Start Over

Run Code

plot <- g_lineplot(

df = adlb_f,

alt_counts_df = adsl_f,

interval = "mean_sdi",

whiskers = c("mean_sdi_lwr", "mean_sdi_upr"),

title = "Plot of Mean (+/-SD)",

subtitle = "Laboratory Test:"

)

plot

_webr_editor_4 = Object {code: "plot <- g_lineplot(\n df = adlb_f,\n alt_counts_df… (+/-SD)\",\n subtitle = \"Laboratory Test:\"\n)\nplot", options: Object, indicator: Ke}

Preview
Try this using WebR

Code

plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  control = control_analyze_vars(conf_level = 0.80),
  title = "Plot of Mean and 80% Confidence Limits by Visit",
  subtitle = "Laboratory Test:"
)
plot

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.

R Code

Start Over

Run Code

plot <- g_lineplot(

df = adlb_f,

alt_counts_df = adsl_f,

control = control_analyze_vars(conf_level = 0.80),

title = "Plot of Mean and 80% Confidence Limits by Visit",

subtitle = "Laboratory Test:"

)

plot

_webr_editor_5 = Object {code: "plot <- g_lineplot(\n df = adlb_f,\n alt_counts_df…by Visit\",\n subtitle = \"Laboratory Test:\"\n)\nplot", options: Object, indicator: Ke}

Preview
Try this using WebR

Code

plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  table = "n",
  subtitle = "Laboratory Test:"
)
plot

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.

R Code

Start Over

Run Code

plot <- g_lineplot(

df = adlb_f,

alt_counts_df = adsl_f,

table = "n",

subtitle = "Laboratory Test:"

)

plot

_webr_editor_6 = Object {code: "plot <- g_lineplot(\n df = adlb_f,\n alt_counts_df…ble = \"n\",\n subtitle = \"Laboratory Test:\"\n)\nplot", options: Object, indicator: Ke}

Preview
Try this using WebR

Code

plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  table = c("n", "mean", "mean_ci"),
  subtitle = "Laboratory Test:"
)
plot

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.

R Code

Start Over

Run Code

plot <- g_lineplot(

df = adlb_f,

alt_counts_df = adsl_f,

table = c("n", "mean", "mean_ci"),

subtitle = "Laboratory Test:"

)

plot

_webr_editor_7 = Object {code: "plot <- g_lineplot(\n df = adlb_f,\n alt_counts_df…mean_ci\"),\n subtitle = \"Laboratory Test:\"\n)\nplot", options: Object, indicator: Ke}

This option is not supported.

Preview
Try this using WebR

Code

plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  whiskers = "mean_ci_upr",
  subtitle = "Laboratory Test:"
)
plot

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.

R Code

Start Over

Run Code

plot <- g_lineplot(

df = adlb_f,

alt_counts_df = adsl_f,

whiskers = "mean_ci_upr",

subtitle = "Laboratory Test:"

)

plot

_webr_editor_8 = Object {code: "plot <- g_lineplot(\n df = adlb_f,\n alt_counts_df…n_ci_upr\",\n subtitle = \"Laboratory Test:\"\n)\nplot", options: Object, indicator: Ke}

Code

library(dplyr)
library(tern)
library(nestcolor)

adsl <- random.cdisc.data::cadsl
adlb <- random.cdisc.data::cadlb
advs <- random.cdisc.data::cadvs

adsl_f <- adsl %>%
  filter(SAFFL == "Y") %>%
  df_explicit_na()

adlb_f <- adlb %>%
  mutate(AVISIT = forcats::fct_reorder(AVISIT, AVISITN, min)) %>%
  dplyr::filter(
    SAFFL == "Y",
    ANL01FL == "Y",
    ONTRTFL == "Y",
    PARAMCD == "ALT",
    AVISIT != "SCREENING"
  ) %>%
  droplevels() %>%
  df_explicit_na()

advs_f <- advs %>%
  mutate(AVISIT = forcats::fct_reorder(AVISIT, AVISITN, min)) %>%
  dplyr::filter(
    SAFFL == "Y",
    ONTRTFL == "Y",
    PARAMCD == "DIABP",
    AVISIT != "SCREENING"
  ) %>%
  droplevels() %>%
  df_explicit_na()

Code

library(teal.modules.clinical)

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

  ADSL <- random.cdisc.data::cadsl
  ADLB <- random.cdisc.data::cadlb %>%
    mutate(AVISIT = fct_reorder(AVISIT, AVISITN, min))
})
datanames <- c("ADSL", "ADLB")
datanames(data) <- datanames

Warning: `datanames<-()` was deprecated in teal.data 0.7.0.
ℹ invalid to use `datanames()<-` or `names()<-` on an object of class
  `teal_data`. See ?names.teal_data

Code

join_keys(data) <- default_cdisc_join_keys[datanames]

## Reusable Configuration For Modules
ADSL <- data[["ADSL"]]
ADLB <- data[["ADLB"]]

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_g_lineplot(
      label = "LINE PLOT",
      dataname = "ADLB",
      strata = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD", "ACTARMCD")),
        "ARM"
      ),
      y = choices_selected(
        variable_choices(ADLB, c("AVAL", "BASE", "CHG", "PCHG")),
        "AVAL"
      ),
      param = choices_selected(
        value_choices(ADLB, "PARAMCD", "PARAM"),
        "ALT"
      )
    )
  )
)

Warning: The `strata` argument of `tm_g_lineplot()` is deprecated as of
teal.modules.clinical 0.9.1. Please use the `group_var` argument instead.

Code

shinyApp(app$ui, app$server)

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.

Reproducibility

Timestamp

[1] "2025-03-26 18:03:32 UTC"

Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.4.2 (2024-10-31)
 os       Ubuntu 24.04.1 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2025-03-26
 pandoc   3.6.3 @ /usr/bin/ (via rmarkdown)
 quarto   1.6.42 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package               * version  date (UTC) lib source
 backports               1.5.0    2024-05-23 [1] RSPM
 brio                    1.1.5    2024-04-24 [1] RSPM
 broom                   1.0.7    2024-09-26 [1] RSPM
 bslib                   0.9.0    2025-01-30 [1] RSPM
 cachem                  1.1.0    2024-05-16 [1] RSPM
 callr                   3.7.6    2024-03-25 [1] RSPM
 checkmate               2.3.2    2024-07-29 [1] RSPM
 chromote                0.5.0    2025-03-21 [1] RSPM
 cli                     3.6.4    2025-02-13 [1] RSPM
 coda                    0.19-4.1 2024-01-31 [1] CRAN (R 4.4.2)
 codetools               0.2-20   2024-03-31 [2] CRAN (R 4.4.2)
 colorspace              2.1-1    2024-07-26 [1] RSPM
 cowplot                 1.1.3    2024-01-22 [1] RSPM
 curl                    6.2.2    2025-03-24 [1] RSPM
 digest                  0.6.37   2024-08-19 [1] RSPM
 dplyr                 * 1.1.4    2023-11-17 [1] RSPM
 emmeans                 1.11.0   2025-03-20 [1] RSPM
 estimability            1.5.1    2024-05-12 [1] RSPM
 evaluate                1.0.3    2025-01-10 [1] RSPM
 farver                  2.1.2    2024-05-13 [1] RSPM
 fastmap                 1.2.0    2024-05-15 [1] RSPM
 fontawesome             0.5.3    2024-11-16 [1] RSPM
 forcats               * 1.0.0    2023-01-29 [1] RSPM
 formatR                 1.14     2023-01-17 [1] CRAN (R 4.4.2)
 formatters            * 0.5.10   2025-01-09 [1] RSPM
 geepack                 1.3.12   2024-09-23 [1] RSPM
 generics                0.1.3    2022-07-05 [1] RSPM
 ggplot2                 3.5.1    2024-04-23 [1] RSPM
 glue                    1.8.0    2024-09-30 [1] RSPM
 gtable                  0.3.6    2024-10-25 [1] RSPM
 htmltools               0.5.8.1  2024-04-04 [1] RSPM
 htmlwidgets             1.6.4    2023-12-06 [1] RSPM
 httpuv                  1.6.15   2024-03-26 [1] RSPM
 jquerylib               0.1.4    2021-04-26 [1] RSPM
 jsonlite                1.9.1    2025-03-03 [1] RSPM
 knitr                   1.50     2025-03-16 [1] RSPM
 labeling                0.4.3    2023-08-29 [1] RSPM
 later                   1.4.1    2024-11-27 [1] RSPM
 lattice                 0.22-6   2024-03-20 [2] CRAN (R 4.4.2)
 lifecycle               1.0.4    2023-11-07 [1] RSPM
 logger                  0.4.0    2024-10-22 [1] RSPM
 magrittr              * 2.0.3    2022-03-30 [1] RSPM
 MASS                    7.3-65   2025-02-28 [2] CRAN (R 4.4.2)
 Matrix                  1.7-3    2025-03-11 [1] CRAN (R 4.4.2)
 memoise                 2.0.1    2021-11-26 [1] RSPM
 mime                    0.13     2025-03-17 [1] RSPM
 multcomp                1.4-28   2025-01-29 [1] RSPM
 munsell                 0.5.1    2024-04-01 [1] RSPM
 mvtnorm                 1.3-3    2025-01-10 [1] RSPM
 nestcolor             * 0.1.3    2025-01-21 [1] RSPM
 nlme                    3.1-167  2025-01-27 [2] CRAN (R 4.4.2)
 pillar                  1.10.1   2025-01-07 [1] RSPM
 pkgcache                2.2.3    2024-09-12 [1] RSPM
 pkgconfig               2.0.3    2019-09-22 [1] RSPM
 processx                3.8.6    2025-02-21 [1] RSPM
 promises                1.3.2    2024-11-28 [1] RSPM
 ps                      1.9.0    2025-02-18 [1] RSPM
 purrr                   1.0.4    2025-02-05 [1] RSPM
 R6                      2.6.1    2025-02-15 [1] RSPM
 ragg                    1.3.3    2024-09-11 [1] RSPM
 random.cdisc.data       0.3.16   2024-10-10 [1] RSPM
 rbibutils               2.3      2024-10-04 [1] RSPM
 Rcpp                    1.0.14   2025-01-12 [1] RSPM
 Rdpack                  2.6.3    2025-03-16 [1] RSPM
 rlang                   1.1.5    2025-01-17 [1] RSPM
 rmarkdown               2.29     2024-11-04 [1] RSPM
 rtables               * 0.6.11   2025-01-10 [1] RSPM
 sandwich                3.1-1    2024-09-15 [1] RSPM
 sass                    0.4.9    2024-03-15 [1] RSPM
 scales                  1.3.0    2023-11-28 [1] RSPM
 sessioninfo             1.2.3    2025-02-05 [1] any (@1.2.3)
 shiny                 * 1.10.0   2024-12-14 [1] RSPM
 shinycssloaders         1.1.0    2024-07-30 [1] RSPM
 shinyjs                 2.1.0    2021-12-23 [1] RSPM
 shinyvalidate           0.1.3    2023-10-04 [1] RSPM
 shinyWidgets            0.9.0    2025-02-21 [1] RSPM
 stringi                 1.8.4    2024-05-06 [1] RSPM
 stringr                 1.5.1    2023-11-14 [1] RSPM
 survival                3.8-3    2024-12-17 [2] CRAN (R 4.4.2)
 systemfonts             1.2.1    2025-01-20 [1] RSPM
 teal                  * 0.16.0   2025-02-23 [1] RSPM
 teal.code             * 0.6.1    2025-02-14 [1] RSPM
 teal.data             * 0.7.0    2025-01-28 [1] RSPM
 teal.logger             0.3.2    2025-02-14 [1] RSPM
 teal.modules.clinical * 0.10.0   2025-02-28 [1] RSPM
 teal.reporter           0.4.0    2025-01-24 [1] RSPM
 teal.slice            * 0.6.0    2025-02-03 [1] RSPM
 teal.transform        * 0.6.0    2025-02-12 [1] RSPM
 teal.widgets            0.4.3    2025-01-31 [1] RSPM
 tern                  * 0.9.7    2025-01-17 [1] RSPM
 tern.gee                0.1.5    2024-08-23 [1] RSPM
 testthat                3.2.3    2025-01-13 [1] RSPM
 textshaping             1.0.0    2025-01-20 [1] RSPM
 TH.data                 1.1-3    2025-01-17 [1] RSPM
 tibble                  3.2.1    2023-03-20 [1] RSPM
 tidyr                   1.3.1    2024-01-24 [1] RSPM
 tidyselect              1.2.1    2024-03-11 [1] RSPM
 vctrs                   0.6.5    2023-12-01 [1] RSPM
 webshot                 0.5.5    2023-06-26 [1] CRAN (R 4.4.2)
 webshot2                0.1.1    2023-08-11 [1] RSPM
 websocket               1.4.2    2024-07-22 [1] RSPM
 withr                   3.0.2    2024-10-28 [1] RSPM
 xfun                    0.51     2025-02-19 [1] RSPM
 xtable                  1.8-4    2019-04-21 [1] RSPM
 yaml                    2.3.10   2024-07-26 [1] RSPM
 zoo                     1.8-13   2025-02-22 [1] RSPM

 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library
 [3] /github/home/R/x86_64-pc-linux-gnu-library/4.4
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

`.lock` file

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

Download

Downloading webR

Output

teal App

Reproducibility

Timestamp

Session Info

.lock file

`teal` App

`.lock` file