Nothing
inst/shiny/ui.R
In StepReg: Stepwise Regression Analysis
source("utils.R")
js <- "
$(document).ready(function() {
$('.navbar .container-fluid .navbar-nav .dropdown .dropdown-menu').prepend(
'<li><a href=\"https://cran.r-project.org/web/packages/StepReg/vignettes/StepReg.html\" target=\"_blank\">Tutorial</a></li>',
'<li><a href=\"https://github.com/JunhuiLi1017/StepReg/issues/new\" target=\"_blank\">Report Bug</a></li>');
});
"
ui <- tagList(
useShinyjs(),
tags$script(HTML(js)),
tags$head(
tags$style(HTML("
/* this will affect all the pre elements */
pre {
color: red;
background-color: #5ef4fb;
}
/* this will affect only the pre elements under the class myclass */
.textOutput pre {
color: black;
background-color: white;
}"))
),
navbarPage(
title = tags$a(href = "https://cran.r-project.org/web/packages/StepReg/index.html", "StepReg"),
theme = shinythemes::shinytheme("flatly"),
# Define tabs within the navbar
tabPanel(
title = "File",
# Sidebar layout with input and output definitions ----
sidebarLayout(
# Sidebar panel for inputs ----
sidebarPanel(
selectInput(
"example_dataset",
label = tags$span(
"Select an example dataset",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c(
"Recommended Regression Type and Dependent Variable for Each Dataset (Demo Purposes)",
"------------------------------------------------------",
"Dataset\t|\tType\t\t|\tResponse",
"------------------------------------------------------",
"mtcars\t|\tlinear\t|\tmpg",
"remission\t|\tlogit\t\t|\tremiss",
"lung\t\t|\tcox\t\t|\ttime and status",
"creditCard\t|\tpoisson\t|\treports",
"------------------------------------------------------"), collapse = "\n"
)
)
),
choices = c(
"",
"mtcars",
"remission",
"lung",
"creditCard")
),
# Input: Select a file ----
fileInput(
"upload_file",
"Or upload your data",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
# Input: Checkbox if file has header
checkboxInput("header", "Header", TRUE),
# Input: Select separator ----
radioButtons(
"sep",
"Separator",
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ","),
# Input: Select quotes ----
radioButtons("quote", "Quote",
choices = c(None = "",
"Double Quote" = '"',
"Single Quote" = "'")),
uiOutput("colname_in_numeric"),
uiOutput("colname_in_factor"),
uiOutput("colname_in_integer"),
uiOutput("colname_in_character"),
actionButton("change_class", "Change class")
),
# Main panel for displaying outputs ----
mainPanel(
tabsetPanel(
tabPanel(
"Data",
div(style = "width: 100%;",
withSpinner(DT::dataTableOutput('tbl', width = 750))
)
), # Data dalam tabel
tabPanel(
"Summary",
div(class="textOutput",
withSpinner(verbatimTextOutput("summary"))
)
),
tabPanel(
title = "Plot",
fluidPage(
sidebarLayout(
sidebarPanel(
selectInput("plot_type",
"select plot type:",
choices = c("Bar plot",
"Box plot",
"Correlation plot",
"Density plot",
"Dot plot",
#"Pairs plot",
"Histogram",
"QQ plot",
"Scatter and Line plot"),
selected = "Correlation plot"),
#h5("select variables for the Plot:"),
selectInput("var_plot",
"Select variables for the Plot:",
choices = "",
multiple = TRUE),
tags$div(
style = "display: flex; justify-content: space-between;",
actionButton("make_plot",
"Run",
icon = icon("chart-line"),
style = "width: 80px; font-size: 10px;"),
downloadButton("downloadPlot",
"Save",
icon = icon("download"),
style = "width: 80px; font-size: 10px;")
)
),
mainPanel(
withSpinner(plotOutput("Plot"))
)
)
)
)
)
)
)
),
tabPanel(
"Analyze",
# p("To perform stepwise regression, you need to first specify the type of
# stepwise procedure, which involves determining the dependent variables by
# defining the scope of both dependent and independent variables. Next,
# select one or more selection strategies and metrics to guide the stepwise
# regression process."),
sidebarLayout(
sidebarPanel(
# Select type (linear, logit, cox, poisson, gamma, or negbin)
selectInput(
"type",
"Regression type:",
choices = c("linear",
"logit",
"cox",
"poisson",
"gamma",
"negbin")
),
# Select dependent variable
conditionalPanel(
condition = "input.type === 'cox'",
selectInput("status", "Status variable:", choices = NULL),
selectInput("time", "Time Variable:", choices = NULL)
),
conditionalPanel(
condition = "input.type === 'linear'",
selectInput("dependent_linear", "Dependent variable:", choices = NULL, multiple = TRUE)
),
conditionalPanel(
condition = "input.type === 'logit' || input.type === 'poisson' || input.type === 'gamma' || input.type === 'negbin'",
selectInput("dependent_glm", "Dependent variable:", choices = NULL)
),
selectInput(
"independent",
"Independent Variables:",
choices = NULL,
multiple = TRUE
),
selectInput(
"include",
"Include Variables:",
choices = NULL,
multiple = TRUE
),
conditionalPanel(
condition = "input.type !== 'cox'",
checkboxInput(
"intercept",
"Include Intercept",
TRUE
)
),
# Select method (forward, backward, or both)
selectInput(
"strategy",
"Stepwise Strategy:",
choices = c("forward",
"backward",
"bidirection",
"subset"),
multiple = TRUE
),
# Select metric
conditionalPanel(
condition = "input.type === 'linear' && input.dependent_linear.length == 1",
selectInput(
"metric_univariate_linear",
"Selection Metric:",
choices = c("AIC",
"AICc",
"BIC",
"CP",
"HQ",
"IC(1)",
"IC(3/2)",
"SBC",
"SL",
"Rsq",
"adjRsq"),
multiple = TRUE
)
),
conditionalPanel(
condition = "input.type === 'linear' && input.dependent_linear.length > 1",
selectInput(
"metric_multivariate_linear",
"Selection Metric:",
choices = c("AIC",
"AICc",
"HQ",
"SL"),
multiple = TRUE
)
),
conditionalPanel(
condition = "input.type !== 'linear'",
selectInput(
"metric_glm_cox",
"Selection Metric:",
choices = c("AIC",
"AICc",
"HQ",
"IC(1)",
"IC(3/2)",
"SBC",
"SL"),
multiple = TRUE
)
),
# Display sliderInput for significance level only when SL is selected
conditionalPanel(
condition = "input.type === 'linear' && input.metric_multivariate_linear.indexOf('SL') != -1",
selectInput(
"Approx_F",
label = "Approx F test statistic:",
choices = c("Pillai",
"Wilks",
"Hotelling-Lawley",
"Roy"),
selected = "Pillai"
)
),
conditionalPanel(
condition = "input.type === 'logit' || input.type === 'gamma' || input.type === 'poisson' || input.type === 'negbin'",
selectInput(
"glm_test",
label = "Test Method",
choices = c("Rao",
"LRT"),
selected = "Rao"
)
),
conditionalPanel(
condition = "input.type === 'cox'",
selectInput(
"cox_test",
label = "Test Method",
choices = c('efron',
'breslow',
'exact'),
selected = "efron"
)
),
# Display sliderInput for significance level only when SL is selected
conditionalPanel(
condition = "input.metric_univariate_linear.indexOf('SL') != -1 && (input.strategy.indexOf('forward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type === 'linear'",
sliderInput(
"sle",
label = tags$span(
"significance level for entry",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under forward and bidirection strategy. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tRao or LRT Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05
)
),
conditionalPanel(
condition = "input.metric_univariate_linear.indexOf('SL') != -1 && (input.strategy.indexOf('backward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type === 'linear'",
sliderInput(
"sls",
label = tags$span(
"significance level for stay",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under backward and bidirection strategy. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tWald Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05
)
),
conditionalPanel(
condition = "input.metric_multivariate_linear.indexOf('SL') != -1 && (input.strategy.indexOf('forward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type === 'linear'",
sliderInput(
"sle",
label = tags$span(
"significance level for entry",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under forward and bidirection strategy.. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tRao or LRT Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05
)
),
conditionalPanel(
condition = "input.metric_multivariate_linear.indexOf('SL') != -1 && (input.strategy.indexOf('backward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type === 'linear'",
sliderInput(
"sls",
label = tags$span(
"significance level for stay",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under backward and bidirection strategy. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tWald Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05)
),
conditionalPanel(
condition = "input.metric_glm_cox.indexOf('SL') != -1 && (input.strategy.indexOf('forward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type !== 'linear'",
sliderInput(
"sle",
label = tags$span(
"significance level for entry",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under forward and bidirection strategy.. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tRao or LRT Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05)
),
conditionalPanel(
condition = "input.metric_glm_cox.indexOf('SL') != -1 && (input.strategy.indexOf('backward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type !== 'linear'",
sliderInput(
"sls",
label = tags$span(
"significance level for stay",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under backward and bidirection strategy. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tWald Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05)
),
tags$div(
style = "display: flex; justify-content: space-between;",
actionButton("run_analysis",
"Run",
icon = icon("chart-line"),
style = "width: 130px; font-size: 12px;"),
downloadButton("download",
"Report",
icon = icon("download"),
style = "width: 130px; font-size: 12px;")
)
),
mainPanel(
tabsetPanel(
tabPanel(
"Statistics",
conditionalPanel(
condition = "input.run_analysis",
htmlOutput("selectionStatText")
),
div(class="textOutput",
withSpinner(verbatimTextOutput("modelSelection"))
)
),
tabPanel(
title = "Visualization",
fluidPage(
fluidRow(
column(
width = 12,
sidebarPanel(
selectInput("strategy_plot",
"Stepwise Strategy:",
choices = c("")),
selectInput("relative_height",
label = tags$span(
"Relative height of plots",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c(
"Adjust the height of plot B relative to plot A"), collapse = "\n"
)
)
),
choices = c(seq(0.2,1,0.2),seq(1.5,4,0.5)),
selected = 1),
downloadButton("download_process_plot",
"Save",
icon = icon("download"),
style = "width: 80px; font-size: 10px;")
)
)
),
fluidRow(
column(width = 12,
mainPanel(
conditionalPanel(
condition = "input.run_analysis",
htmlOutput("selectionPlotText")
),
withSpinner(plotOutput("detail_plot"))
)
)
)
)
),
tabPanel(
"Model Vote",
conditionalPanel(
condition = "input.run_analysis",
htmlOutput("modelVoteText")
),
withSpinner(DT::dataTableOutput("modelVote"))
)
)
)
)
),
navbarMenu(
title = "Help",
tabPanel(
"Citation",
tags$p("If you think 'StepReg' R package is helpful to your research, please cite:"),
tags$ul(
tags$li("Junhui Li (2024). StepReg: Stepwise Regression Analysis. R package version 1.5.1, https://CRAN.R-project.org/package=StepReg")
)
)
)
)
)
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source("utils.R")
js <- "
$(document).ready(function() {
$('.navbar .container-fluid .navbar-nav .dropdown .dropdown-menu').prepend(
'<li><a href=\"https://cran.r-project.org/web/packages/StepReg/vignettes/StepReg.html\" target=\"_blank\">Tutorial</a></li>',
'<li><a href=\"https://github.com/JunhuiLi1017/StepReg/issues/new\" target=\"_blank\">Report Bug</a></li>');
});
"
ui <- tagList(
useShinyjs(),
tags$script(HTML(js)),
tags$head(
tags$style(HTML("
/* this will affect all the pre elements */
pre {
color: red;
background-color: #5ef4fb;
}
/* this will affect only the pre elements under the class myclass */
.textOutput pre {
color: black;
background-color: white;
}"))
),
navbarPage(
title = tags$a(href = "https://cran.r-project.org/web/packages/StepReg/index.html", "StepReg"),
theme = shinythemes::shinytheme("flatly"),
# Define tabs within the navbar
tabPanel(
title = "File",
# Sidebar layout with input and output definitions ----
sidebarLayout(
# Sidebar panel for inputs ----
sidebarPanel(
selectInput(
"example_dataset",
label = tags$span(
"Select an example dataset",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c(
"Recommended Regression Type and Dependent Variable for Each Dataset (Demo Purposes)",
"------------------------------------------------------",
"Dataset\t|\tType\t\t|\tResponse",
"------------------------------------------------------",
"mtcars\t|\tlinear\t|\tmpg",
"remission\t|\tlogit\t\t|\tremiss",
"lung\t\t|\tcox\t\t|\ttime and status",
"creditCard\t|\tpoisson\t|\treports",
"------------------------------------------------------"), collapse = "\n"
)
)
),
choices = c(
"",
"mtcars",
"remission",
"lung",
"creditCard")
),
# Input: Select a file ----
fileInput(
"upload_file",
"Or upload your data",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
# Input: Checkbox if file has header
checkboxInput("header", "Header", TRUE),
# Input: Select separator ----
radioButtons(
"sep",
"Separator",
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ","),
# Input: Select quotes ----
radioButtons("quote", "Quote",
choices = c(None = "",
"Double Quote" = '"',
"Single Quote" = "'")),
uiOutput("colname_in_numeric"),
uiOutput("colname_in_factor"),
uiOutput("colname_in_integer"),
uiOutput("colname_in_character"),
actionButton("change_class", "Change class")
),
# Main panel for displaying outputs ----
mainPanel(
tabsetPanel(
tabPanel(
"Data",
div(style = "width: 100%;",
withSpinner(DT::dataTableOutput('tbl', width = 750))
)
), # Data dalam tabel
tabPanel(
"Summary",
div(class="textOutput",
withSpinner(verbatimTextOutput("summary"))
)
),
tabPanel(
title = "Plot",
fluidPage(
sidebarLayout(
sidebarPanel(
selectInput("plot_type",
"select plot type:",
choices = c("Bar plot",
"Box plot",
"Correlation plot",
"Density plot",
"Dot plot",
#"Pairs plot",
"Histogram",
"QQ plot",
"Scatter and Line plot"),
selected = "Correlation plot"),
#h5("select variables for the Plot:"),
selectInput("var_plot",
"Select variables for the Plot:",
choices = "",
multiple = TRUE),
tags$div(
style = "display: flex; justify-content: space-between;",
actionButton("make_plot",
"Run",
icon = icon("chart-line"),
style = "width: 80px; font-size: 10px;"),
downloadButton("downloadPlot",
"Save",
icon = icon("download"),
style = "width: 80px; font-size: 10px;")
)
),
mainPanel(
withSpinner(plotOutput("Plot"))
)
)
)
)
)
)
)
),
tabPanel(
"Analyze",
# p("To perform stepwise regression, you need to first specify the type of
# stepwise procedure, which involves determining the dependent variables by
# defining the scope of both dependent and independent variables. Next,
# select one or more selection strategies and metrics to guide the stepwise
# regression process."),
sidebarLayout(
sidebarPanel(
# Select type (linear, logit, cox, poisson, gamma, or negbin)
selectInput(
"type",
"Regression type:",
choices = c("linear",
"logit",
"cox",
"poisson",
"gamma",
"negbin")
),
# Select dependent variable
conditionalPanel(
condition = "input.type === 'cox'",
selectInput("status", "Status variable:", choices = NULL),
selectInput("time", "Time Variable:", choices = NULL)
),
conditionalPanel(
condition = "input.type === 'linear'",
selectInput("dependent_linear", "Dependent variable:", choices = NULL, multiple = TRUE)
),
conditionalPanel(
condition = "input.type === 'logit' || input.type === 'poisson' || input.type === 'gamma' || input.type === 'negbin'",
selectInput("dependent_glm", "Dependent variable:", choices = NULL)
),
selectInput(
"independent",
"Independent Variables:",
choices = NULL,
multiple = TRUE
),
selectInput(
"include",
"Include Variables:",
choices = NULL,
multiple = TRUE
),
conditionalPanel(
condition = "input.type !== 'cox'",
checkboxInput(
"intercept",
"Include Intercept",
TRUE
)
),
# Select method (forward, backward, or both)
selectInput(
"strategy",
"Stepwise Strategy:",
choices = c("forward",
"backward",
"bidirection",
"subset"),
multiple = TRUE
),
# Select metric
conditionalPanel(
condition = "input.type === 'linear' && input.dependent_linear.length == 1",
selectInput(
"metric_univariate_linear",
"Selection Metric:",
choices = c("AIC",
"AICc",
"BIC",
"CP",
"HQ",
"IC(1)",
"IC(3/2)",
"SBC",
"SL",
"Rsq",
"adjRsq"),
multiple = TRUE
)
),
conditionalPanel(
condition = "input.type === 'linear' && input.dependent_linear.length > 1",
selectInput(
"metric_multivariate_linear",
"Selection Metric:",
choices = c("AIC",
"AICc",
"HQ",
"SL"),
multiple = TRUE
)
),
conditionalPanel(
condition = "input.type !== 'linear'",
selectInput(
"metric_glm_cox",
"Selection Metric:",
choices = c("AIC",
"AICc",
"HQ",
"IC(1)",
"IC(3/2)",
"SBC",
"SL"),
multiple = TRUE
)
),
# Display sliderInput for significance level only when SL is selected
conditionalPanel(
condition = "input.type === 'linear' && input.metric_multivariate_linear.indexOf('SL') != -1",
selectInput(
"Approx_F",
label = "Approx F test statistic:",
choices = c("Pillai",
"Wilks",
"Hotelling-Lawley",
"Roy"),
selected = "Pillai"
)
),
conditionalPanel(
condition = "input.type === 'logit' || input.type === 'gamma' || input.type === 'poisson' || input.type === 'negbin'",
selectInput(
"glm_test",
label = "Test Method",
choices = c("Rao",
"LRT"),
selected = "Rao"
)
),
conditionalPanel(
condition = "input.type === 'cox'",
selectInput(
"cox_test",
label = "Test Method",
choices = c('efron',
'breslow',
'exact'),
selected = "efron"
)
),
# Display sliderInput for significance level only when SL is selected
conditionalPanel(
condition = "input.metric_univariate_linear.indexOf('SL') != -1 && (input.strategy.indexOf('forward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type === 'linear'",
sliderInput(
"sle",
label = tags$span(
"significance level for entry",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under forward and bidirection strategy. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tRao or LRT Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05
)
),
conditionalPanel(
condition = "input.metric_univariate_linear.indexOf('SL') != -1 && (input.strategy.indexOf('backward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type === 'linear'",
sliderInput(
"sls",
label = tags$span(
"significance level for stay",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under backward and bidirection strategy. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tWald Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05
)
),
conditionalPanel(
condition = "input.metric_multivariate_linear.indexOf('SL') != -1 && (input.strategy.indexOf('forward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type === 'linear'",
sliderInput(
"sle",
label = tags$span(
"significance level for entry",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under forward and bidirection strategy.. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tRao or LRT Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05
)
),
conditionalPanel(
condition = "input.metric_multivariate_linear.indexOf('SL') != -1 && (input.strategy.indexOf('backward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type === 'linear'",
sliderInput(
"sls",
label = tags$span(
"significance level for stay",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under backward and bidirection strategy. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tWald Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05)
),
conditionalPanel(
condition = "input.metric_glm_cox.indexOf('SL') != -1 && (input.strategy.indexOf('forward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type !== 'linear'",
sliderInput(
"sle",
label = tags$span(
"significance level for entry",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under forward and bidirection strategy.. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tRao or LRT Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05)
),
conditionalPanel(
condition = "input.metric_glm_cox.indexOf('SL') != -1 && (input.strategy.indexOf('backward') != -1 || input.strategy.indexOf('bidirection') != -1) && input.type !== 'linear'",
sliderInput(
"sls",
label = tags$span(
"significance level for stay",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c("Cut-off for 'SL' metric under backward and bidirection strategy. Depending on the type of regression, different tests will be employed to compute the corresponding P-values.",
"------------------------------------------------------",
"Type\t\t\t\t|\t\t\t\tTest",
"------------------------------------------------------",
"linear(univariate)\t|\tF test",
"linear(multivariate)\t|\tApprox F test",
"logit/poission/gamma\t|\tWald Chi-squared",
"cox\t\t\t\t|\tWald Chi-squared",
"------------------------------------------------------"), collapse = "\n")
)
),
min = 0,
max = 1,
value = 0.05)
),
tags$div(
style = "display: flex; justify-content: space-between;",
actionButton("run_analysis",
"Run",
icon = icon("chart-line"),
style = "width: 130px; font-size: 12px;"),
downloadButton("download",
"Report",
icon = icon("download"),
style = "width: 130px; font-size: 12px;")
)
),
mainPanel(
tabsetPanel(
tabPanel(
"Statistics",
conditionalPanel(
condition = "input.run_analysis",
htmlOutput("selectionStatText")
),
div(class="textOutput",
withSpinner(verbatimTextOutput("modelSelection"))
)
),
tabPanel(
title = "Visualization",
fluidPage(
fluidRow(
column(
width = 12,
sidebarPanel(
selectInput("strategy_plot",
"Stepwise Strategy:",
choices = c("")),
selectInput("relative_height",
label = tags$span(
"Relative height of plots",
tags$i(
class = "glyphicon glyphicon-question-sign centered-icon",
style = "color:#0072B2;",
title = paste(c(
"Adjust the height of plot B relative to plot A"), collapse = "\n"
)
)
),
choices = c(seq(0.2,1,0.2),seq(1.5,4,0.5)),
selected = 1),
downloadButton("download_process_plot",
"Save",
icon = icon("download"),
style = "width: 80px; font-size: 10px;")
)
)
),
fluidRow(
column(width = 12,
mainPanel(
conditionalPanel(
condition = "input.run_analysis",
htmlOutput("selectionPlotText")
),
withSpinner(plotOutput("detail_plot"))
)
)
)
)
),
tabPanel(
"Model Vote",
conditionalPanel(
condition = "input.run_analysis",
htmlOutput("modelVoteText")
),
withSpinner(DT::dataTableOutput("modelVote"))
)
)
)
)
),
navbarMenu(
title = "Help",
tabPanel(
"Citation",
tags$p("If you think 'StepReg' R package is helpful to your research, please cite:"),
tags$ul(
tags$li("Junhui Li (2024). StepReg: Stepwise Regression Analysis. R package version 1.5.1, https://CRAN.R-project.org/package=StepReg")
)
)
)
)
)
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