MMRMG01

Plots for Mixed-Effect Model Repeated Measures Analysis

Given an MMRM fitted with s_mmrm, g_mmrm_lsmeans displays for each visit the adjusted means within group and/or difference in adjusted means between groups. g_mmrm_diagnostic displays marginal residual plots for evaluating model fit.

:::: {.panel-tabset} and
Model Fitting


Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Loading required package: tern

Loading required package: rtables

Loading required package: formatters


Attaching package: 'formatters'

The following object is masked from 'package:base':

    %||%

Loading required package: magrittr


Attaching package: 'rtables'

The following object is masked from 'package:utils':

    str

Registered S3 method overwritten by 'tern':
  method   from 
  tidy.glm broom

mmrm() registered as emmeans extension

Least Squares Means:
Estimates Within Groups

Considering the treatment variable in the model

Code

plot <- g_mmrm_lsmeans(
  mmrm_results,
  select = "estimates",
  xlab = "Visit"
)
plot

Considering the treatment variable in the model, with lines

Code

plot <- g_mmrm_lsmeans(
  mmrm_results,
  select = "estimates",
  xlab = "Visit",
  show_lines = TRUE
)
plot

Considering the treatment variable in the model, with statistics table

Code

plot <- g_mmrm_lsmeans(
  mmrm_results,
  select = "estimates",
  xlab = "Visit",
  table_stats = c("n", "estimate", "se", "ci"),
  table_font_size = 4,
  table_rel_height = 0.6
)
plot

Least Squares Means:
Contrasts Between Groups

Users can choose to display both estimates and contrasts together by running g_mmrm_lsmeans(mmrm_results).

Code

plot <- g_mmrm_lsmeans(
  mmrm_results,
  select = "contrasts",
  titles = c(contrasts = "Contrasts of FKSI-FWB means"),
  xlab = "Visit"
)

Coordinate system already present. Adding new coordinate system, which will
replace the existing one.

Code

plot

Model Diagnostics: Marginal
Fitted Values vs. Residuals

Code

plot <- g_mmrm_diagnostic(mmrm_results)
plot

Model Diagnostics: Normality
of Marginal Residuals

Code

plot <- g_mmrm_diagnostic(mmrm_results, type = "q-q-residual")
plot

Data Setup and
Model Fitting

Code

library(dplyr)
library(tern.mmrm)
library(nestcolor)

adsl <- random.cdisc.data::cadsl
adqs <- random.cdisc.data::cadqs

adqs_f <- adqs %>%
  dplyr::filter(PARAMCD == "FKSI-FWB" & !AVISIT %in% c("BASELINE")) %>%
  droplevels() %>%
  dplyr::mutate(ARM = factor(ARM, levels = c("B: Placebo", "A: Drug X", "C: Combination"))) %>%
  dplyr::mutate(AVISITN = rank(AVISITN) %>% as.factor() %>% as.numeric() %>% as.factor())

mmrm_results <- fit_mmrm(
  vars = list(
    response = "AVAL",
    covariates = c("STRATA2"),
    id = "USUBJID",
    arm = "ARM",
    visit = "AVISIT"
  ),
  data = adqs_f
)

::::

`teal` App

Code

library(teal.modules.clinical)

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

  ADSL <- random.cdisc.data::cadsl
  ADQS <- random.cdisc.data::cadqs %>%
    filter(ABLFL != "Y" & ABLFL2 != "Y") %>%
    filter(AVISIT %in% c("WEEK 1 DAY 8", "WEEK 2 DAY 15", "WEEK 3 DAY 22")) %>%
    mutate(
      AVISIT = as.factor(AVISIT),
      AVISITN = rank(AVISITN) %>%
        as.factor() %>%
        as.numeric() %>%
        as.factor() # making consecutive numeric factor
    )
})
datanames <- c("ADSL", "ADQS")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

arm_ref_comp <- list(
  ARMCD = list(
    ref = "ARM A",
    comp = c("ARM B", "ARM C")
  )
)

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

## Setup App
app <- init(
  data = data,
  modules = modules(
    tm_a_mmrm(
      label = "MMRM",
      dataname = "ADQS",
      aval_var = choices_selected(c("AVAL", "CHG"), "AVAL"),
      id_var = choices_selected(c("USUBJID", "SUBJID"), "USUBJID"),
      arm_var = choices_selected(c("ARM", "ARMCD"), "ARMCD"),
      visit_var = choices_selected(c("AVISIT", "AVISITN"), "AVISIT"),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        choices = value_choices(ADQS, "PARAMCD", "PARAM"),
        selected = "FKSI-FWB"
      ),
      cov_var = choices_selected(c("BASE", "AGE", "SEX", "BASE:AVISIT"), NULL),
      conf_level = choices_selected(c(0.95, 0.9, 0.8), 0.95)
    )
  )
)

shinyApp(app$ui, app$server)

Reproducibility

Timestamp

[1] "2024-11-02 17:33:40 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)
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 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)
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 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)
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 htmlwidgets             1.6.4       2023-12-06 [1] CRAN (R 4.4.1)
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 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)
 labeling                0.4.3       2023-08-29 [1] CRAN (R 4.4.1)
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 lattice                 0.22-6      2024-03-20 [2] CRAN (R 4.4.1)
 lifecycle               1.0.4       2023-11-07 [1] CRAN (R 4.4.1)
 logger                  0.3.0       2024-03-05 [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)
 mmrm                    0.3.14      2024-09-27 [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)
 nestcolor             * 0.1.2.9017  2024-11-02 [1] git2r (https://github.com/insightsengineering/nestcolor.git@3d2ce62)
 nlme                    3.1-166     2024-08-14 [2] CRAN (R 4.4.1)
 parallelly              1.38.0      2024-07-27 [1] 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)
 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                      1.8.0       2024-09-12 [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       0.3.16.9001 2024-11-02 [1] git2r (https://github.com/insightsengineering/random.cdisc.data.git@a65bfbe)
 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               * 0.6.10.9002 2024-11-02 [1] git2r (https://github.com/insightsengineering/rtables.git@d2cc7a0)
 sandwich                3.1-1       2024-09-15 [1] CRAN (R 4.4.1)
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 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)
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 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                  * 0.15.2.9079 2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.git@53c423d)
 teal.code             * 0.5.0.9012  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.code.git@86aa265)
 teal.data             * 0.6.0.9015  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.data.git@eca9695)
 teal.logger             0.3.0.9000  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.logger.git@cd9cc7e)
 teal.modules.clinical * 0.9.1.9030  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.modules.clinical.git@5cf76ac)
 teal.reporter           0.3.1.9016  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.reporter.git@4fefa7e)
 teal.slice            * 0.5.1.9015  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.slice.git@25f4101)
 teal.transform        * 0.5.0.9015  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.transform.git@0b855e3)
 teal.widgets            0.4.2.9022  2024-11-02 [1] git2r (https://github.com/insightsengineering/teal.widgets.git@8a39dd4)
 tern                  * 0.9.6.9013  2024-11-02 [1] git2r (https://github.com/insightsengineering/tern.git@435fd51)
 tern.gee                0.1.5.9004  2024-11-02 [1] git2r (https://github.com/insightsengineering/tern.gee.git@458172d)
 tern.mmrm             * 0.3.2.9002  2024-11-02 [1] git2r (https://github.com/insightsengineering/tern.mmrm.git@a4254e8)
 testthat                3.2.1.1     2024-04-14 [1] CRAN (R 4.4.1)
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 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

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

`.lock` file

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

Download

Least Squares Means: Estimates Within Groups

Considering the treatment variable in the model

Considering the treatment variable in the model, with lines

Considering the treatment variable in the model, with statistics table

Least Squares Means: Contrasts Between Groups

Model Diagnostics: Marginal Fitted Values vs. Residuals

Model Diagnostics: Normality of Marginal Residuals

Data Setup and Model Fitting

teal App

Reproducibility

Timestamp

Session Info

.lock file

Least Squares Means:
Estimates Within Groups

Least Squares Means:
Contrasts Between Groups

Model Diagnostics: Marginal
Fitted Values vs. Residuals

Model Diagnostics: Normality
of Marginal Residuals

Data Setup and
Model Fitting

`teal` App

`.lock` file