TLG Catalog - Stable
  • Stable
    • Dev
  1. Graphs
  2. Other
  3. MNG01
  • Introduction

  • Tables
    • ADA
      • ADAT01
      • ADAT02
      • ADAT03
      • ADAT04A
      • ADAT04B
    • Adverse Events
      • AET01
      • AET01_AESI
      • AET02
      • AET02_SMQ
      • AET03
      • AET04
      • AET04_PI
      • AET05
      • AET05_ALL
      • AET06
      • AET06_SMQ
      • AET07
      • AET09
      • AET09_SMQ
      • AET10
    • Concomitant Medications
      • CMT01
      • CMT01A
      • CMT01B
      • CMT02_PT
    • Deaths
      • DTHT01
    • Demography
      • DMT01
    • Disclosures
      • DISCLOSUREST01
      • EUDRAT01
      • EUDRAT02
    • Disposition
      • DST01
      • PDT01
      • PDT02
    • ECG
      • EGT01
      • EGT02
      • EGT03
      • EGT04
      • EGT05_QTCAT
    • Efficacy
      • AOVT01
      • AOVT02
      • AOVT03
      • CFBT01
      • CMHT01
      • COXT01
      • COXT02
      • DORT01
      • LGRT02
      • MMRMT01
      • ONCT05
      • RATET01
      • RBMIT01
      • RSPT01
      • TTET01
    • Exposure
      • EXT01
    • Lab Results
      • LBT01
      • LBT02
      • LBT03
      • LBT04
      • LBT05
      • LBT06
      • LBT07
      • LBT08
      • LBT09
      • LBT10
      • LBT10_BL
      • LBT11
      • LBT11_BL
      • LBT12
      • LBT12_BL
      • LBT13
      • LBT14
      • LBT15
    • Medical History
      • MHT01
    • Pharmacokinetic
      • PKCT01
      • PKPT02
      • PKPT03
      • PKPT04
      • PKPT05
      • PKPT06
      • PKPT07
      • PKPT08
      • PKPT11
    • Risk Management Plan
      • RMPT01
      • RMPT03
      • RMPT04
      • RMPT05
      • RMPT06
    • Safety
      • ENTXX
    • Vital Signs
      • VST01
      • VST02
  • Listings
    • ADA
      • ADAL02
    • Adverse Events
      • AEL01
      • AEL01_NOLLT
      • AEL02
      • AEL02_ED
      • AEL03
      • AEL04
    • Concomitant Medications
      • CML01
      • CML02A_GL
      • CML02B_GL
    • Development Safety Update Report
      • DSUR4
    • Disposition
      • DSL01
      • DSL02
    • ECG
      • EGL01
    • Efficacy
      • ONCL01
    • Exposure
      • EXL01
    • Lab Results
      • LBL01
      • LBL01_RLS
      • LBL02A
      • LBL02A_RLS
      • LBL02B
    • Medical History
      • MHL01
    • Pharmacokinetic
      • ADAL01
      • PKCL01
      • PKCL02
      • PKPL01
      • PKPL02
      • PKPL04
    • Vital Signs
      • VSL01
  • Graphs
    • Efficacy
      • FSTG01
      • FSTG02
      • KMG01
      • MMRMG01
      • MMRMG02
    • Other
      • BRG01
      • BWG01
      • CIG01
      • IPPG01
      • LTG01
      • MNG01
    • Pharmacokinetic
      • PKCG01
      • PKCG02
      • PKCG03
      • PKPG01
      • PKPG02
      • PKPG03
      • PKPG04
      • PKPG06

  • Appendix
    • Reproducibility

  • Index

On this page

  • Output
  • teal App
  • Reproducibility
    • Timestamp
    • Session Info
    • .lock file
  • Edit this page
  • Report an issue
  1. Graphs
  2. Other
  3. MNG01

MNG01

Mean Plot


Output

  • Plot of Mean
    and CI
  • Plot of Mean and CIs of Change
    from Baseline (Changing the Input
    Analysis Data Set and Analysis Variable)
  • Plot of Mean (+/-SD)
    (Changing the Statistics)
  • Plot of Mean and CI
    (Modify Alpha Level)
  • Plot of Mean and CI (with Number
    of Patients only in Table Section)
  • Plot of Mean and CI
    (with Table Section)
  • Plot of Median and CI (Visits
    Condensed in Table Section)
  • Plot of Mean and
    Upper Confidence Limit
  • Data Setup
  • Preview
  • Try this using WebR
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.

  • Preview
  • Try this using WebR
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.

  • 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.

  • 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.

  • 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.

  • 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.

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.

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()

teal App

  • Preview
  • Try this using shinylive
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.

#| '!! shinylive warning !!': |
#|   shinylive does not work in self-contained HTML documents.
#|   Please set `embed-resources: false` in your metadata.
#| 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)
  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
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"
      )
    )
  )
)

shinyApp(app$ui, app$server)

Reproducibility

Timestamp

[1] "2025-07-05 18:03:18 UTC"

Session Info

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.5.0 (2025-04-11)
 os       Ubuntu 24.04.2 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2025-07-05
 pandoc   3.7.0.2 @ /usr/bin/ (via rmarkdown)
 quarto   1.7.32 @ /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                   1.0.8    2025-03-28 [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                0.5.1    2025-04-24 [1] RSPM
 cli                     3.6.5    2025-04-23 [1] RSPM
 coda                    0.19-4.1 2024-01-31 [1] CRAN (R 4.5.0)
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 curl                    6.4.0    2025-06-22 [1] RSPM
 dichromat               2.0-0.1  2022-05-02 [1] CRAN (R 4.5.0)
 digest                  0.6.37   2024-08-19 [1] RSPM
 dplyr                 * 1.1.4    2023-11-17 [1] RSPM
 emmeans                 1.11.1   2025-05-04 [1] RSPM
 estimability            1.5.1    2024-05-12 [1] RSPM
 evaluate                1.0.4    2025-06-18 [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
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 formatR                 1.14     2023-01-17 [1] CRAN (R 4.5.0)
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 generics                0.1.4    2025-05-09 [1] RSPM
 ggplot2                 3.5.2    2025-04-09 [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
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 jquerylib               0.1.4    2021-04-26 [1] RSPM
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 MASS                    7.3-65   2025-02-28 [2] CRAN (R 4.5.0)
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 mvtnorm                 1.3-3    2025-01-10 [1] RSPM
 nestcolor             * 0.1.3    2025-01-21 [1] RSPM
 nlme                    3.1-168  2025-03-31 [2] CRAN (R 4.5.0)
 pillar                  1.11.0   2025-07-04 [1] RSPM
 pkgcache                2.2.4    2025-05-26 [1] RSPM
 pkgconfig               2.0.3    2019-09-22 [1] RSPM
 processx                3.8.6    2025-02-21 [1] RSPM
 promises                1.3.3    2025-05-29 [1] RSPM
 ps                      1.9.1    2025-04-12 [1] RSPM
 purrr                   1.0.4    2025-02-05 [1] RSPM
 R6                      2.6.1    2025-02-15 [1] RSPM
 ragg                    1.4.0    2025-04-10 [1] RSPM
 random.cdisc.data       0.3.16   2024-10-10 [1] RSPM
 rbibutils               2.3      2024-10-04 [1] RSPM
 RColorBrewer            1.1-3    2022-04-03 [1] RSPM
 Rcpp                    1.1.0    2025-07-02 [1] RSPM
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 rlang                   1.1.6    2025-04-11 [1] RSPM
 rmarkdown               2.29     2024-11-04 [1] RSPM
 rtables               * 0.6.13   2025-06-19 [1] RSPM
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 sass                    0.4.10   2025-04-11 [1] RSPM
 scales                  1.4.0    2025-04-24 [1] RSPM
 sessioninfo             1.2.3    2025-02-05 [1] any (@1.2.3)
 shiny                 * 1.11.1   2025-07-03 [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                 1.8.7    2025-03-27 [1] RSPM
 stringr                 1.5.1    2023-11-14 [1] RSPM
 survival                3.8-3    2024-12-17 [2] CRAN (R 4.5.0)
 systemfonts             1.2.3    2025-04-30 [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                  * 0.9.9    2025-06-20 [1] RSPM
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 [1] /usr/local/lib/R/site-library
 [2] /usr/local/lib/R/library
 [3] /github/home/R/x86_64-pc-linux-gnu-library/4.5
 * ── 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

LTG01
PKCG01
Source Code
---
title: MNG01
subtitle: Mean Plot
---

------------------------------------------------------------------------

{{< include ../../_utils/envir_hook.qmd >}}

```{r setup, echo = FALSE, warning = FALSE, message = FALSE}
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()
```

```{r include = FALSE}
webr_code_labels <- c("setup")
```

{{< include ../../_utils/webr_no_include.qmd >}}

## Output

:::::::::: panel-tabset
## Plot of Mean <br/> and CI

::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview

```{r plot1, test = list(plot_v1 = "plot")}
plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  subtitle = "Laboratory Test:"
)
plot
```

```{r include = FALSE}
webr_code_labels <- c("plot1")
```

{{< include ../../_utils/webr.qmd >}}
:::

## Plot of Mean and CIs of Change <br/> from Baseline (Changing the Input <br/> Analysis Data Set and Analysis Variable)

::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview

```{r plot2, test = list(plot_v2 = "plot")}
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
```

```{r include = FALSE}
webr_code_labels <- c("plot2")
```

{{< include ../../_utils/webr.qmd >}}
:::

## Plot of Mean (+/-SD) <br/> (Changing the Statistics)

::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview

```{r plot3, test = list(plot_v3 = "plot")}
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
```

```{r include = FALSE}
webr_code_labels <- c("plot3")
```

{{< include ../../_utils/webr.qmd >}}
:::

## Plot of Mean and CI <br/> (Modify Alpha Level)

::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview

```{r plot4, test = list(plot_v4 = "plot")}
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
```

```{r include = FALSE}
webr_code_labels <- c("plot4")
```

{{< include ../../_utils/webr.qmd >}}
:::

## Plot of Mean and CI (with Number <br/> of Patients only in Table Section)

::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview

```{r plot5, test = list(plot_v5 = "plot")}
plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  table = "n",
  subtitle = "Laboratory Test:"
)
plot
```

```{r include = FALSE}
webr_code_labels <- c("plot5")
```

{{< include ../../_utils/webr.qmd >}}
:::

## Plot of Mean and CI <br/> (with Table Section)

::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview

```{r plot6, fig.height = 8, test = list(plot_v6 = "plot")}
plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  table = c("n", "mean", "mean_ci"),
  subtitle = "Laboratory Test:"
)
plot
```

```{r include = FALSE}
webr_code_labels <- c("plot6")
```

{{< include ../../_utils/webr.qmd >}}
:::

## Plot of Median and CI (Visits <br/> Condensed in Table Section)

This option is not supported.

## Plot of Mean and <br/> Upper Confidence Limit

::: {.panel-tabset .nav-justified group="webr"}
## {{< fa regular file-lines sm fw >}} Preview

```{r plot7, test = list(plot_v7 = "plot")}
plot <- g_lineplot(
  df = adlb_f,
  alt_counts_df = adsl_f,
  whiskers = "mean_ci_upr",
  subtitle = "Laboratory Test:"
)
plot
```

```{r include = FALSE}
webr_code_labels <- c("plot7")
```

{{< include ../../_utils/webr.qmd >}}
:::

## Data Setup

```{r setup}
#| code-fold: show
```
::::::::::

{{< include ../../_utils/save_results.qmd >}}

## `teal` App

::: {.panel-tabset .nav-justified}
## {{< fa regular file-lines fa-sm fa-fw >}} Preview

```{r teal, opts.label = c("skip_if_testing", "app"), eval = packageVersion("teal.modules.clinical") > "0.9.1"}
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
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"
      )
    )
  )
)

shinyApp(app$ui, app$server)
```

{{< include ../../_utils/shinylive.qmd >}}
:::

{{< include ../../repro.qmd >}}

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