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app.R
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library(shiny)
# devtools::install_github("milanwiedemann/lcsm")
# devtools::install_github("hadley/emo")
library(emo)
library(lcsm)
library(lavaan)
library(dplyr)
library(ggplot2)
library(ggpubr)
library(DT)
# ui ----
ui <- tagList(
tags$head(
HTML(
"<script>
(function(i,s,o,g,r,a,m){
i['GoogleAnalyticsObject']=r;i[r]=i[r]||
function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();
a=s.createElement(o), m=s.getElementsByTagName(o)[0];
a.async=1;
a.src=g;m.parentNode.insertBefore(a,m)
})
(window, document, 'script',
'//www.google-analytics.com/analytics.js','ga');
ga('create', 'UA-113145816-2', 'auto');
ga('send', 'pageview');
</script>"
)
),
navbarPage(
"shinychange",
# Overview ----
tabPanel(paste0("Overview ", emo::ji("books")),
includeMarkdown("INCLUDEME.md")),
# Simulate Data ----
# Generate univariate LCSM ----
navbarMenu(
"Generate lavaan Syntax",
tabPanel(
"Univariate LCSM",
column(width = 3,
h4("Options:"),
tabsetPanel(
tabPanel(
"Data Characteristics",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
numericInput(
"specify_uni_timepoints",
"Measurement Points:",
value = 5,
min = 2
),
helpText("Note: Number of repeated measurement points."),
textInput("specify_uni_var_name", "Variable Name:", value = "x"),
helpText(
"Note: Variable name to be used for generating lavaan syntax, changes wont show on the path diagram.
Variable name should start with a letter."
)
)
),
tabPanel(
"Select Parameters",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
checkboxGroupInput(
"specify_uni_param",
label = "Construct X",
choices = list(
"Constant change factor [alpha_g]" = "alpha_constant",
"Proportional change factor [beta_x]" = "beta",
"Autoregression of change scores [phi_x]" = "phi"
),
selected = c("alpha_constant", "beta", "phi")
)
)
)
)),
column(9,
h4("Results:"),
tabsetPanel(
tabPanel(
"lavaan Syntax",
helpText(
"Note: lavaan syntax for the selected data characteristics and model parameters.
This syntax includes comments describing the different sections of the model and can be modified by hand.
Modified syntax could be used in the 'model' argument of functions from the lavaan package.
Observed scores in the syntax are the variable name followed by a number indicating the measurement point.
Latent true scores have the prefix 'l' (for latent) followed by the variable name of the observed score.
Change scores have the prefix 'd' (for delta) followed by the variable name of the observed score."
),
verbatimTextOutput("lavaan_uni_lcsm")
),
tabPanel(
"Path Diagram",
helpText(),
# just a placeholder for a little bit top margin
# wellPanel(
fluidRow(column(
4,
checkboxInput(
"plot_specify_uni_lcsm_path_whatLabels",
"Show the parameter names as labels",
value = TRUE,
width = NULL
)
),
column(
4,
checkboxInput(
"plot_specify_uni_lcsm_path_colorgroups",
"I like rainbows",
value = FALSE,
width = NULL
)
)),
fluidRow(column(
8,
plotOutput(
"plot_specify_uni_lcsm_path",
width = 900,
height = 550
)
)),
hr(
"Reference: Sacha Epskamp (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages' Output. R package version 1.1.2.
https://CRAN.R-project.org/package=semPlot."
)
)
))
),
# Generate bivariate LCSM ----
tabPanel(
"Bivariate LCSM",
column(width = 3,
h4("Options:"),
tabsetPanel(
tabPanel(
"Data Characteristics",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
numericInput(
"specify_bi_timepoints",
"Measurement Points:",
value = 5,
min = 2
),
helpText("Note: Number of repeated measurement points for each construct.")
),
wellPanel(
textInput("specify_bi_var_name_x", "Variable Name Construct X:", value = "x"),
textInput("specify_var_name_y", "Variable Name Construct Y:", value = "y"),
helpText(
"Note: Variable names to be used for generating lavaan syntax, changes wont show on the path diagram.
Variable names should start with a letter."
)
)
),
tabPanel(
"Select Parameters",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
checkboxGroupInput(
"specify_bi_param_x",
label = "Construct X:",
choices = list(
"Constant change factor [alpha_g]" = "alpha_constant_x",
"Proportional change factor [beta_x]" = "beta_x",
"Autoregression of change scores [phi_x]" = "phi_x"
),
selected = c("alpha_constant_x", "beta_x", "phi_x")
)
),
wellPanel(
checkboxGroupInput(
"specify_bi_param_y",
label = "Construct Y:",
choices = list(
"Constant change factor [alpha_j]" = "alpha_constant_y",
"Proportional change factor [beta_y]" = "beta_y",
"Autoregression of change scores [phi_y]" = "phi_y"
),
selected = c("alpha_constant_y", "beta_y", "phi_y")
)
),
wellPanel(
checkboxGroupInput(
"specify_bi_param_coupling",
label = "Coupling:",
choices = list(
"Change score x (t) determined by true score y (t) [delta_con_xy]" = "delta_con_xy",
"Change score y (t) determined by true score x (t) [delta_con_yx]" = "delta_con_yx",
"Change score x (t) determined by true score y (t-1) [delta_lag_xy]" = "delta_lag_xy",
"Change score y (t) determined by true score x (t-1) [delta_lag_yx]" = "delta_lag_yx",
"Change score x (t) determined by change score y (t) [xi_con_xy]" = "xi_con_xy",
"Change score y (t) determined by change score x (t) [xi_con_yx]" = "xi_con_yx",
"Change score x (t) determined by change score y (t-1) [xi_lag_xy]" = "xi_lag_xy",
"Change score y (t) determined by change score x (t-1) [xi_lag_yx]" = "xi_lag_yx"
)
)
)
)
)),
column(9,
h4("Results:"),
tabsetPanel(
tabPanel(
"lavaan Syntax",
helpText(
"Note: lavaan syntax for the selected data characteristics and model parameters.
This syntax includes comments describing the different sections of the model and can be modified by hand.
Modified syntax could be used in the 'model' argument of functions from the lavaan package.
Observed scores in the syntax are the variable name followed by a number indicating the measurement point.
Latent true scores have the prefix 'l' (for latent) followed by the variable name of the observed score.
Change scores have the prefix 'd' (for delta) followed by the variable name of the observed score."
),
verbatimTextOutput("lavaan_bi_lcsm")
),
tabPanel(
"Path Diagram",
helpText(),
# just a placeholder for a little bit top margin
# wellPanel(
fluidRow(column(
4,
checkboxInput(
"plot_specify_bi_lcsm_path_whatLabels",
"Show the parameter names as labels",
value = TRUE,
width = NULL
)
),
column(
4,
checkboxInput(
"plot_specify_bi_lcsm_path_colorgroups",
"I like rainbows",
value = FALSE,
width = NULL
)
)),
fluidRow(column(
8,
plotOutput(
"plot_specify_bi_lcsm_path",
width = 900,
height = 550
)
)),
hr(
"Reference: Sacha Epskamp (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages' Output. R package version 1.1.2.
https://CRAN.R-project.org/package=semPlot."
)
)
))
)
),
navbarMenu(
"Simulate Data",
# Simulate Univariate ----
tabPanel(
"Univariate LCSM",
column(
width = 4,
h4("Options:"),
tabsetPanel(
tabPanel(
"Data Characteristics",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
numericInput("sim_uni_timepoints", "Measurement Points:", value = 7),
numericInput("sim_uni_samplesize", "Sample Size:", value = 500),
sliderInput(
"sim_uni_na_x_pct",
"Missingness in %:",
min = 0,
max = 100,
value = 0,
step = 1
),
helpText("Note: Missing values are added randomly after simulating data.")
# Maybe have a Simulate Data button at some point?
# actionButton("simulate_action", "Simulate Data", class = "btn-primary")
)
),
# Enter Parameters ----
tabPanel(
"Set Parameters",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
helpText(
"Note: See 'Help' for further information about the parameters.
Example parameters in the input fields below were taken from Grimm, Ram & Estabrook (2017), Chapter 16."
),
numericInput(
"sim_uni_gamma_lx1",
"gamma_lx1",
value = 32.53,
step = .1
),
numericInput(
"sim_uni_sigma2_lx1",
"sigma2_lx1",
value = 71.9,
step = .1
),
numericInput(
"sim_uni_sigma2_ux",
"sigma2_ux",
value = 30.82,
step = .1
),
numericInput(
"sim_uni_beta_x",
"beta_x",
value = -0.24,
step = .1
),
numericInput(
"sim_uni_alpha_g2",
"alpha_g2",
value = 15.22,
step = .1
),
numericInput(
"sim_uni_sigma2_g2",
"sigma2_g2",
value = 5.6,
step = .1
),
numericInput(
"sim_uni_sigma_g2lx1",
"sigma_g2lx1",
value = 13.75,
step = .1
),
numericInput("sim_uni_phi_x",
"phi_x",
value = NA,
step = .1)
)
),
tabPanel("Help",
helpText(), # just a placeholder for a little bit top margin
includeMarkdown("INCLUDEME_UNI.md"))
)
),
column(
width = 8,
h4("Results:"),
tabsetPanel(
tabPanel(
"Simulated Data",
DT::dataTableOutput("datatable_sim_uni_lcsm"),
downloadButton("download_uni_data", "Download")
),
tabPanel(
"Longitudinal Plot",
plotOutput("plot_sim_uni_lcsm"),
hr(
"Reference: Hadley Wickham (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York."
)
),
tabPanel(
"lavaan Syntax",
helpText(
"Note: The lavaan syntax below was used to simulate the data using the function simulateData() from the R package lavaan.
Observed scores in the syntax are the variable name followed by a number indicating the measurement point.
Latent true scores have the prefix 'l' (for latent) followed by the variable name of the observed score.
Change scores have the prefix 'd' (for delta) followed by the variable name of the observed score."
),
verbatimTextOutput("lavaan_sim_uni_lcsm")
),
# Maybe include tab with simplified Path Diagram?
tabPanel(
"Path Diagram",
helpText(),
# just a placeholder for a little bit top margin
# wellPanel(
fluidRow(column(
4,
checkboxInput(
"plot_sim_uni_lcsm_path_whatLabels",
"Show the parameter names as labels",
value = TRUE,
width = NULL
)
),
column(
4,
checkboxInput(
"plot_sim_uni_lcsm_path_colorgroups",
"I like rainbows",
value = FALSE,
width = NULL
)
)),
fluidRow(column(
8,
plotOutput(
"plot_sim_uni_lcsm_path",
width = 900,
height = 550
)
)),
hr(
"Reference: Sacha Epskamp (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages' Output. R package version 1.1.2.
https://CRAN.R-project.org/package=semPlot."
)
)
)
)
),
# Simulate Bivariate ----
tabPanel(
"Bivariate LCSM",
column(
width = 4,
h4("Options:"),
tabsetPanel(
tabPanel(
"Data Characteristics",
helpText(),
wellPanel(
numericInput(
"sim_bi_timepoints",
"Measurement Points:",
value = 7,
min = 2
),
numericInput("sim_bi_samplesize", "Sample Size:", value = 500),
sliderInput(
"sim_bi_na_x_pct",
"Missingness Construct X in % :",
min = 0,
max = 100,
value = 0,
step = 1
),
sliderInput(
"sim_bi_na_y_pct",
"Missingness Construct Y in % :",
min = 0,
max = 100,
value = 0,
step = 1
),
helpText("Note: Missing values are added randomly after simulating data."),
)
),
# Enter Parameters ----
tabPanel("Set Parameters",
tabsetPanel(
tabPanel(
"Construct X",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
helpText(
"Note: See 'Help' for further information about the parameters.
Example parameters in the input fields below were taken from Grimm, Ram & Estabrook (2017), Chapter 17."
),
numericInput(
"sim_bi_gamma_lx1",
"gamma_lx1",
value = 32.52,
step = .1
),
numericInput(
"sim_bi_sigma2_lx1",
"sigma2_lx1",
value = 72.73,
step = .1
),
numericInput(
"sim_bi_sigma2_ux",
"sigma2_ux",
value = 31.44,
step = .1
),
numericInput(
"sim_bi_beta_x",
"beta_x",
value = -.30,
step = .1
),
numericInput(
"sim_bi_alpha_g2",
"alpha_g2",
value = 15.20,
step = .1
),
numericInput(
"sim_bi_sigma2_g2",
"sigma2_g2",
value = 5.79,
step = .1
),
numericInput(
"sim_bi_sigma_g2lx1",
"sigma_g2lx1",
value = 14.46,
step = .1
),
numericInput("sim_bi_phi_x",
"phi_x",
value = NA,
step = .1)
)
),
tabPanel(
"Construct Y",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
helpText(
"Note: See 'Help' for further information about the parameters.
Example parameters in the input fields below were taken from Grimm, Ram & Estabrook (2017), Chapter 17."
),
numericInput(
"sim_bi_gamma_ly1",
"gamma_ly1",
value = 34.36,
step = .1
),
numericInput(
"sim_bi_sigma2_ly1",
"sigma2_ly1",
value = 72.26,
step = .1
),
numericInput(
"sim_bi_sigma2_uy",
"sigma2_uy",
value = 33.34,
step = .1
),
numericInput(
"sim_bi_beta_y",
"beta_y",
value = -.49,
step = .1
),
numericInput(
"sim_bi_alpha_j2",
"alpha_j2",
value = 10.99,
step = .1
),
numericInput(
"sim_bi_sigma2_j2",
"sigma2_j2",
value = 17.85,
step = .1
),
numericInput(
"sim_bi_sigma_j2ly1",
"sigma_j2ly1",
value = 25.98,
step = .1
),
numericInput("sim_bi_phi_y",
"phi_y",
value = NA,
step = .1)
)
),
tabPanel(
"Coupling",
helpText(),
wellPanel(
helpText(
"Note: See 'Help' for further information about the parameters.
Example parameters in the input fields below were taken from Grimm, Ram & Estabrook (2017), Chapter 17."
),
numericInput(
"sim_bi_sigma_su",
"sigma_su",
value = 6.46,
step = .1
),
numericInput(
"sim_bi_sigma_ly1lx1",
"sigma_ly1lx1",
value = 57.34,
step = .1
),
numericInput(
"sim_bi_sigma_g2ly1",
"sigma_g2ly1",
value = 10.04,
step = .1
),
numericInput(
"sim_bi_sigma_j2lx1",
"sigma_j2lx1",
value = 25.98,
step = .1
),
numericInput(
"sim_bi_sigma_j2g2",
"sigma_j2g2",
value = .79,
step = .1
),
numericInput(
"sim_bi_delta_lag_xy",
"delta_lag_xy",
value = 0.05,
step = .1
),
numericInput(
"sim_bi_delta_lag_yx",
"delta_lag_yx",
value = 0.38,
step = .1
),
numericInput(
"sim_bi_xi_lag_xy",
"xi_lag_xy",
value = NA,
step = .1
),
numericInput(
"sim_bi_xi_lag_yx",
"xi_lag_yx",
value = NA,
step = .1
),
)
)
)),
tabPanel("Help",
tabsetPanel(
tabPanel(
"Construct X",
helpText(),
# just a placeholder for a little bit top margin
includeMarkdown("INCLUDEME_BI_X.md")
),
tabPanel(
"Construct Y",
helpText(),
# just a placeholder for a little bit top margin
includeMarkdown("INCLUDEME_BI_Y.md")
),
tabPanel("Coupling",
helpText(), # just a placeholder for a little bit top margin
includeMarkdown("INCLUDEME_BI_C.md"))
))
)
),
column(
width = 8,
h4("Results:"),
tabsetPanel(
tabPanel(
"Simulated Data",
DT::dataTableOutput("datatable_sim_bi_lcsm"),
downloadButton("download_bi_data", "Download")
),
tabPanel(
"Longitudinal Plots",
plotOutput("plot_sim_bi_lcsm", width = 850, height = 550),
hr(
"Reference: Hadley Wickham (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York."
)
),
tabPanel(
"lavaan Syntax",
helpText(
"Note: The lavaan syntax below was used to simulate the data using the function simulateData() from the R package lavaan.
Observed scores in the syntax are the variable name followed by a number indicating the measurement point.
Latent true scores have the prefix 'l' (for latent) followed by the variable name of the observed score.
Change scores have the prefix 'd' (for delta) followed by the variable name of the observed score."
),
verbatimTextOutput("lavaan_sim_bi_lcsm")
),
# Maybe include tab with simplified Path Diagram?
tabPanel(
"Path Diagram",
helpText(),
# just a placeholder for a little bit top margin
# wellPanel(
fluidRow(column(
4,
checkboxInput(
"plot_sim_bi_lcsm_path_whatLabels",
"Show the parameter names as labels",
value = TRUE,
width = NULL
)
),
column(
4,
checkboxInput(
"plot_sim_bi_lcsm_path_colorgroups",
"I like rainbows",
value = FALSE,
width = NULL
)
)),
fluidRow(column(
8,
plotOutput("plot_sim_bi_lcsm_path", width = 900, height = 550)
)),
hr(
"Reference: Sacha Epskamp (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages' Output. R package version 1.1.2.
https://CRAN.R-project.org/package=semPlot."
)
)
)
)
)
),
# Fit univariate LCSM ----
navbarMenu(
"Fit Model",
tabPanel(
"Univariate LCSM",
column(
width = 4,
h4("Options:"),
tabsetPanel(
tabPanel(
"Load Data",
helpText(),
wellPanel(
helpText(
"Note: Select a CSV file or load the example data by ticking the box at the bottom."
),
# Input: Select a file ---
fileInput(
"file_uni",
"Select CSV File",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
# textInput(inputId = "file_uni_url",
# label = "Load CSV from URL",
# placeholder = "Enter URL to CSV file here"
# ),
# Input: Checkbox if file has header ---
checkboxInput("header", "Variable names included", TRUE),
# Input: Select separator ---
radioButtons(
"uni_sep",
"Separator",
choices = c(
"Comma" = ",",
"Semicolon" = ";",
"Tab" = "\t"
),
selected = ","
),
# Input: Select quotes ---
radioButtons(
"uni_quote",
"Quote",
choices = c(
None = "",
"Double Quote" = '"',
"Single Quote" = "'"
),
selected = '"'
)
),
wellPanel(
checkboxInput("uni_sample_data_check", "Load Example Data 1", FALSE),
# make this radio buttins, second example could be a url, e.g. grimm data
# do same for bivariate models ....
# checkboxInput("uni_sample2_data_check", "Load Example Data 2", FALSE),
helpText(
"Note: Tick this box to select the example data set."
)
)
),
tabPanel(
"Select Variables",
helpText(),
wellPanel(
selectInput(
"uni_select_id",
"Select ID Variable:",
c("Variable 1", "Variable 2", "Variable 3"),
multiple = FALSE
),
selectInput(
"uni_select_vars",
"Select Construct X Variables:",
c("Variable 1", "Variable 2", "Variable 3"),
multiple = TRUE
),
helpText(
"Select variables in the order that reflects the time points they were measured (i.e. variable with values of the first measuresment of construct X is selected first)."
)
)
),
tabPanel(
"Select Parameters",
helpText(),
# just a placeholder for a little bit top margin
wellPanel(
checkboxGroupInput(
"fit_uni_param",
label = "Construct X",
choices = list(
"Constant change factor [alpha_g]" = "alpha_constant",
"Proportional change factor [beta_x]" = "beta",
"Autoregression of change scores [phi_x]" = "phi"
)
)
)
),
tabPanel("Help",
helpText(), # just a placeholder for a little bit top margin
includeMarkdown("INCLUDEME_UNI.md"))
),
actionButton("fit_uni_lcsm_go", "Fit model", class = "btn-primary")
),
column(
8,
h4("Results:"),
tabsetPanel(
tabPanel(
"Data",
helpText(
"Note: Datatable for the selected variables. Values are rounded to the third decimal."
),
DT::dataTableOutput("contents")
),
tabPanel(
"lavaan Syntax",
helpText(
"Note: Based on the selected variables and parameters the lavaan syntax below was used to fit a univariate latent change score model.
The selected variable names were renamed starting with x1 in the order they were selected in the 'Select Construct X Variables' box.
Observed scores in the syntax are 'x' followed by a number indicating the measurement point.
Latent true scores have the prefix 'l' (for latent) followed by the variable name of the observed score.
Change scores have the prefix 'd' (for delta) followed by the variable name of the observed score."
),
verbatimTextOutput("lavaan_fit_uni_lcsm")
),
tabPanel(
"Estimated Parameters",
helpText(
"Click 'Fit model' on the left to fit a univariate LCSM and extract the estimated model parameters."
),
DT::dataTableOutput("fit_uni_lcsm_param"),
hr(
tags$div(
"References:", tags$br(),
"David Robinson and Alex Hayes (2019). broom: Convert Statistical Analysis Objects into Tidy Tibbles. R package version 0.5.2.
https://CRAN.R-project.org/package=broom.", tags$br(),
"Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. URL
http://www.jstatsoft.org/v48/i02/.")
)
),
tabPanel(
"Fit Statistics",
helpText(
"Click 'Fit model' on the left to fit a univariate LCSM and extract the fit statistics."
),
fluidRow(column(
4,
checkboxInput(
"fit_uni_lcsm_fit_stats_details",
"Show details",
value = FALSE,
width = NULL
)
)),
fluidRow(
DT::dataTableOutput("fit_uni_lcsm_fit_stats"),
hr(
tags$div(
"References:", tags$br(),
"David Robinson and Alex Hayes (2019). broom: Convert Statistical Analysis Objects into Tidy Tibbles. R package version 0.5.2.
https://CRAN.R-project.org/package=broom.", tags$br(),
"Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. URL
http://www.jstatsoft.org/v48/i02/.")
)
)
),
tabPanel(
"Longitudinal Plot",
plotOutput("plot_fit_uni_lcsm"),
hr(
"Reference: Hadley Wickham (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York."
)
),
tabPanel(
"Path Diagram",
helpText(),
# just a placeholder for a little bit top margin
# wellPanel(
fluidRow(column(
4,
checkboxInput(
"plot_fit_uni_lcsm_path_whatLabels",
"Show the parameter names as labels",
value = TRUE,
width = NULL
)
),
column(
4,
checkboxInput(
"plot_fit_uni_lcsm_path_colorgroups",
"I like rainbows",
value = FALSE,
width = NULL
)
)),
fluidRow(column(
8,
plotOutput(
"plot_fit_uni_lcsm_path",
width = 900,
height = 550
)
)),
hr(
"Reference: Sacha Epskamp (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages' Output. R package version 1.1.2.
https://CRAN.R-project.org/package=semPlot."
)
)
)
)
),
# Fit bivariate LCSM ----
tabPanel(
"Bivariate LCSM",
column(
width = 4,
h4("Options:"),
tabsetPanel(
tabPanel(
"Load Data",
helpText(),
wellPanel(
helpText(
"Note: Select a CSV file or load the example data by ticking the box at the bottom."
),
# Input: Select a file ---
fileInput(
"file_bi",
"Select CSV File",
multiple = TRUE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
# textInput(inputId = "file_bi_url",
# label = "Load CSV from URL",
# placeholder = "Enter URL to CSV file"
# ),
# Input: Checkbox if file has header ---
checkboxInput("header", "Variable names included", TRUE),
# Input: Select separator ---
radioButtons(
"bi_sep",
"Separator",
choices = c(
"Comma" = ",",
"Semicolon" = ";",
"Tab" = "\t"