Nothing
inst/ClustRandApp/ui.r
In MedianaDesigner: Power and Sample Size Calculations for Clinical Trials
library(shiny)
suppressPackageStartupMessages(library(shinydashboard))
library(MedianaDesigner)
library(shinyMatrix)
shinyUI(
dashboardPage(
dashboardHeader(title = "MedianaDesigner"),
dashboardSidebar(
sidebarMenu(id = "sidebar",
menuItem("Design parameters", tabName = "design_parameters", icon = icon("sliders-h")),
menuItem("Endpoint parameters", tabName = "endpoint_parameters", icon = icon("sliders-h")),
menuItem("General parameters", tabName = "general_parameters", icon = icon("sliders-h")),
menuItem("Simulation results", tabName = "simulation", icon = icon("table")),
menuItem("Simulation report", tabName = "report", icon = icon("file"))
)
),
dashboardBody(
tags$head(
tags$link(rel = "stylesheet", type = "text/css", href = "main.css?2")
),
tabItems(
tabItem(tabName = "design_parameters",
fluidRow(
box(
title = "Cluster-randomized design",
solidHeader = FALSE,
collapsible = FALSE,
width = 12,
"The web application computes key operating characteristics of a cluster-randomized design for a Phase III clinical trial."
)
),
fluidRow(
column(3, class = "col-md-3",
box(
title = "Number of trial arms",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "narms", label = "Number of trial arms", value = 3, min = 2, max = 5),
tags$p(class = "help-block",
"Total number of trial arms, including the control arm.")
)
),
column(9, class = "col-md-9",
box(
title = "Sample size",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
uiOutput("SampleSize"),
tags$p(class = "help-block",
"Number of completers in each trial arm. Completers are defined as patients who complete the trial and are included in the final analysis.")
)
)
),
fluidRow(
column(6, class = "col-md-6",
box(
title = "Cluster scheme",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
selectInput("cluster_index", label = "Cluster scheme",
c("Fixed" = 1, "Random" = 2),
tags$p(class = "help-block",
"A trial design with fixed (pre-defined) or random cluster sizes.")
)
)
)
),
conditionalPanel(
condition = "input.cluster_index == 1",
fluidRow(
column(3, class = "col-md-3",
box(
title = "Cluster sizes in the control arm",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "n_clusters_fixed1", label = "Number of clusters in the control arm", value = 10, min = 5),
uiOutput("ClusterSizeFixed1")
)
),
column(9, class = "col-md-9",
box(
title = "Cluster sizes in the treatment arms",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "n_clusters_fixed2", label = "Number of clusters in each treatment arm", value = 10, min = 5),
uiOutput("ClusterSizeFixed2")
)
)
)
),
conditionalPanel(
condition = "input.cluster_index == 2",
fluidRow(
column(3, class = "col-md-3",
box(
title = "Relative cluster sizes in the control arm",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "n_clusters_random1", label = "Number of clusters in the control arm", value = 10, min = 5),
uiOutput("ClusterSizeRandom1"),
tags$p(class = "help-block",
"The cluster membership in the control arm is determined using a generalized Bernoulli distribution based on the relative cluster sizes.")
)
),
column(9, class = "col-md-9",
box(
title = "Relative cluster sizes in the treatment arms",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "n_clusters_random2", label = "Number of clusters in each treatment arm", value = 10, min = 5),
uiOutput("ClusterSizeRandom2"),
tags$p(class = "help-block",
"The cluster membership in each treatment arm is determined using a generalized Bernoulli distribution based on the relative cluster sizes.")
)
)
)
),
fluidRow(
box(
title = "Next step",
background = "red",
width = 12,
tags$p("Proceed to Endpoint parameters."),
actionButton("jump_to_panel2", "Next tab")
)
)
),
tabItem(tabName = "endpoint_parameters",
fluidRow(
column(3, class = "col-md-3",
box(
title = "Endpoint type",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
selectInput("endpoint_index", label = "Primary endpoint's type",
c("Normal" = 1, "Binary" = 2)),
selectInput("direction_index", label = "Direction of favorable outcome",
c("Higher" = 1, "Lower" = 2))
)
),
column(9, class = "col-md-9",
box(
title = "Treatment effect assumptions",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
uiOutput("TreatmentEffectAssumptions"),
tags$p(class = "help-block",
"Treatment effect assumptions for the selected primary endpoint under the alternative hypothesis of beneficial effect, i.e., the experimental treatment is effective.")
)
)
),
fluidRow(
column(9, class = "col-md-9",
box(
title = "Variability parameters",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
uiOutput("VariabilityParameters")
)
)
),
fluidRow(
box(
title = "Next step",
background = "red",
width = 12,
tags$p("Proceed to General parameters."),
actionButton("jump_to_panel3", "Next tab")
)
)
),
tabItem(tabName = "general_parameters",
fluidRow(
column(6, class = "col-md-6",
box(
title = "Data analysis method",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
selectInput("method_index", label = "Data analysis method",
c("GEE" = 1, "GLMEM" = 2)),
tags$p(class = "help-block",
"GEE: Generalized estimating equations, GLMEM: Generalized linear mixed effects model. The current implementation of the GLMEM method is much less efficient than that for the GEE method and results in longer simulation run times.")
)
),
conditionalPanel(
condition = "input.narms >= 3",
column(6, class = "col-md-6",
box(
title = "Data analysis method",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
selectInput("mult_test", label = "Multiple testing procedure",
c("Bonferroni" = 1, "Holm" = 2, "Hochberg" = 3))
)
)
)
),
fluidRow(
column(6, class = "col-md-6",
box(
title = "Alpha",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "alpha", label = "Type I error rate", value = 0.025),
tags$p(class = "help-block",
"One-sided Type I error rate.")
)
),
column(6, class = "col-md-6",
box(
title = "Number of simulations",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "nsims", label = "Number of simulation runs", value = 1000)
)
)
),
fluidRow(
column(6, class = "col-md-6",
box(
title = "Descriptive statistics",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
checkboxInput("descriptive_statistics", "Compute descriptive statistics", FALSE),
tags$p(class = "help-block",
"Key descriptive statistics (arm-specific effects and cluster sizes) will be computed from each simulation run.")
)
)
),
fluidRow(
box(
title = "Next step",
background = "red",
width = 12,
tags$p("Proceed to Simulation results."),
actionButton("jump_to_panel4", "Next tab")
)
)
),
tabItem(tabName = "simulation",
fluidRow(
box(
title = "Summary of simulation results",
status = "primary",
solidHeader = FALSE,
collapsible = FALSE,
width = 12
),
conditionalPanel(
condition = "input.descriptive_statistics == 1",
column(12, class="col-lg-12",
box(
title = "Descriptive statistics",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
tableOutput("DescriptiveStatistics"),
tags$p(class = "help-block",
"Descriptive statistics computed from each simulation run: 2.5%P (2.5th percentile), 25%P (25th percentile), 75%P (75th percentile) and 97.5%P (97.5th percentile).")
)
)
),
column(12, class="col-lg-12",
box(
title = "Power calculations",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
tableOutput("Power")
)
)
),
fluidRow(
box(
title = "Next step",
background = "red",
width = 12,
tags$p("Proceed to Simulation report."),
actionButton("jump_to_panel5", "Next tab")
)
)
),
tabItem(tabName = "report",
fluidRow(
box(
title = "Create a simulation report",
background = "red",
width = 12,
tags$p("Click the Download button to create and save a detailed simulation report in a Microsoft Word format."),
downloadButton("DownloadResults", "Download")
)
)
)
)
)
)
)
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MedianaDesigner documentation built on Aug. 28, 2023, 9:06 a.m.
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library(shiny)
suppressPackageStartupMessages(library(shinydashboard))
library(MedianaDesigner)
library(shinyMatrix)
shinyUI(
dashboardPage(
dashboardHeader(title = "MedianaDesigner"),
dashboardSidebar(
sidebarMenu(id = "sidebar",
menuItem("Design parameters", tabName = "design_parameters", icon = icon("sliders-h")),
menuItem("Endpoint parameters", tabName = "endpoint_parameters", icon = icon("sliders-h")),
menuItem("General parameters", tabName = "general_parameters", icon = icon("sliders-h")),
menuItem("Simulation results", tabName = "simulation", icon = icon("table")),
menuItem("Simulation report", tabName = "report", icon = icon("file"))
)
),
dashboardBody(
tags$head(
tags$link(rel = "stylesheet", type = "text/css", href = "main.css?2")
),
tabItems(
tabItem(tabName = "design_parameters",
fluidRow(
box(
title = "Cluster-randomized design",
solidHeader = FALSE,
collapsible = FALSE,
width = 12,
"The web application computes key operating characteristics of a cluster-randomized design for a Phase III clinical trial."
)
),
fluidRow(
column(3, class = "col-md-3",
box(
title = "Number of trial arms",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "narms", label = "Number of trial arms", value = 3, min = 2, max = 5),
tags$p(class = "help-block",
"Total number of trial arms, including the control arm.")
)
),
column(9, class = "col-md-9",
box(
title = "Sample size",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
uiOutput("SampleSize"),
tags$p(class = "help-block",
"Number of completers in each trial arm. Completers are defined as patients who complete the trial and are included in the final analysis.")
)
)
),
fluidRow(
column(6, class = "col-md-6",
box(
title = "Cluster scheme",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
selectInput("cluster_index", label = "Cluster scheme",
c("Fixed" = 1, "Random" = 2),
tags$p(class = "help-block",
"A trial design with fixed (pre-defined) or random cluster sizes.")
)
)
)
),
conditionalPanel(
condition = "input.cluster_index == 1",
fluidRow(
column(3, class = "col-md-3",
box(
title = "Cluster sizes in the control arm",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "n_clusters_fixed1", label = "Number of clusters in the control arm", value = 10, min = 5),
uiOutput("ClusterSizeFixed1")
)
),
column(9, class = "col-md-9",
box(
title = "Cluster sizes in the treatment arms",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "n_clusters_fixed2", label = "Number of clusters in each treatment arm", value = 10, min = 5),
uiOutput("ClusterSizeFixed2")
)
)
)
),
conditionalPanel(
condition = "input.cluster_index == 2",
fluidRow(
column(3, class = "col-md-3",
box(
title = "Relative cluster sizes in the control arm",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "n_clusters_random1", label = "Number of clusters in the control arm", value = 10, min = 5),
uiOutput("ClusterSizeRandom1"),
tags$p(class = "help-block",
"The cluster membership in the control arm is determined using a generalized Bernoulli distribution based on the relative cluster sizes.")
)
),
column(9, class = "col-md-9",
box(
title = "Relative cluster sizes in the treatment arms",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "n_clusters_random2", label = "Number of clusters in each treatment arm", value = 10, min = 5),
uiOutput("ClusterSizeRandom2"),
tags$p(class = "help-block",
"The cluster membership in each treatment arm is determined using a generalized Bernoulli distribution based on the relative cluster sizes.")
)
)
)
),
fluidRow(
box(
title = "Next step",
background = "red",
width = 12,
tags$p("Proceed to Endpoint parameters."),
actionButton("jump_to_panel2", "Next tab")
)
)
),
tabItem(tabName = "endpoint_parameters",
fluidRow(
column(3, class = "col-md-3",
box(
title = "Endpoint type",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
selectInput("endpoint_index", label = "Primary endpoint's type",
c("Normal" = 1, "Binary" = 2)),
selectInput("direction_index", label = "Direction of favorable outcome",
c("Higher" = 1, "Lower" = 2))
)
),
column(9, class = "col-md-9",
box(
title = "Treatment effect assumptions",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
uiOutput("TreatmentEffectAssumptions"),
tags$p(class = "help-block",
"Treatment effect assumptions for the selected primary endpoint under the alternative hypothesis of beneficial effect, i.e., the experimental treatment is effective.")
)
)
),
fluidRow(
column(9, class = "col-md-9",
box(
title = "Variability parameters",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
uiOutput("VariabilityParameters")
)
)
),
fluidRow(
box(
title = "Next step",
background = "red",
width = 12,
tags$p("Proceed to General parameters."),
actionButton("jump_to_panel3", "Next tab")
)
)
),
tabItem(tabName = "general_parameters",
fluidRow(
column(6, class = "col-md-6",
box(
title = "Data analysis method",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
selectInput("method_index", label = "Data analysis method",
c("GEE" = 1, "GLMEM" = 2)),
tags$p(class = "help-block",
"GEE: Generalized estimating equations, GLMEM: Generalized linear mixed effects model. The current implementation of the GLMEM method is much less efficient than that for the GEE method and results in longer simulation run times.")
)
),
conditionalPanel(
condition = "input.narms >= 3",
column(6, class = "col-md-6",
box(
title = "Data analysis method",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
selectInput("mult_test", label = "Multiple testing procedure",
c("Bonferroni" = 1, "Holm" = 2, "Hochberg" = 3))
)
)
)
),
fluidRow(
column(6, class = "col-md-6",
box(
title = "Alpha",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "alpha", label = "Type I error rate", value = 0.025),
tags$p(class = "help-block",
"One-sided Type I error rate.")
)
),
column(6, class = "col-md-6",
box(
title = "Number of simulations",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
numericInput(inputId = "nsims", label = "Number of simulation runs", value = 1000)
)
)
),
fluidRow(
column(6, class = "col-md-6",
box(
title = "Descriptive statistics",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
checkboxInput("descriptive_statistics", "Compute descriptive statistics", FALSE),
tags$p(class = "help-block",
"Key descriptive statistics (arm-specific effects and cluster sizes) will be computed from each simulation run.")
)
)
),
fluidRow(
box(
title = "Next step",
background = "red",
width = 12,
tags$p("Proceed to Simulation results."),
actionButton("jump_to_panel4", "Next tab")
)
)
),
tabItem(tabName = "simulation",
fluidRow(
box(
title = "Summary of simulation results",
status = "primary",
solidHeader = FALSE,
collapsible = FALSE,
width = 12
),
conditionalPanel(
condition = "input.descriptive_statistics == 1",
column(12, class="col-lg-12",
box(
title = "Descriptive statistics",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
tableOutput("DescriptiveStatistics"),
tags$p(class = "help-block",
"Descriptive statistics computed from each simulation run: 2.5%P (2.5th percentile), 25%P (25th percentile), 75%P (75th percentile) and 97.5%P (97.5th percentile).")
)
)
),
column(12, class="col-lg-12",
box(
title = "Power calculations",
status = "primary",
solidHeader = TRUE,
collapsible = TRUE,
width = NULL,
tableOutput("Power")
)
)
),
fluidRow(
box(
title = "Next step",
background = "red",
width = 12,
tags$p("Proceed to Simulation report."),
actionButton("jump_to_panel5", "Next tab")
)
)
),
tabItem(tabName = "report",
fluidRow(
box(
title = "Create a simulation report",
background = "red",
width = 12,
tags$p("Click the Download button to create and save a detailed simulation report in a Microsoft Word format."),
downloadButton("DownloadResults", "Download")
)
)
)
)
)
)
)
Try the MedianaDesigner package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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