R/nptest.p1.ui.R

In mephas: Shiny Application of Medical and Pharmaceutical Statistics

##----------#----------#----------#----------
##
## 3MFSnptest UI
##
##    >Panel 1
##
## Language: EN
## 
## DT: 2019-01-09
##
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##---------- Sign Test ----------

##' @title UI of Sign Test (Non-paramatric Tests)
##' @export
nptest.signtest<-function(){

sidebarLayout(


sidebarPanel(

h4("Hypotheses"),

tags$b("Null hypothesis"),
HTML("<p> m = m&#8320: the population median is equal to the specified value </p>"),

radioButtons("alt.st", label = "Alternative hypothesis", 
choiceNames = list(
HTML("m &#8800 m&#8320: the population median of X is not equal to the specified value"),
HTML("m < m&#8320: the population median of X is less than the specified value"),
HTML("m > m&#8320: the population median of X is greater than the specified value")),
choiceValues = list("two.sided", "less", "greater"))),

mainPanel(
h4('Results of Sign Test'), 
tableOutput("sign.test")
)  
)
} 
##---------- Wilcoxon Signed-Rank Test ----------
##' @title UI of Wilcoxon Signed-Rank Test (Non-paramatric Tests)
##' @export
nptest.wstest<-function(){

sidebarLayout(

sidebarPanel(

h4("Hypotheses"),

tags$b("Null hypothesis"),
HTML("<p> m = m&#8320: the population median is equal to the specified value; the distribution of the data set is symmetric about the default value </p>"),

radioButtons("alt.wsr", label = "Alternative hypothesis", 
choiceNames = list(
HTML("m &#8800 m&#8320: the population median of X is not equal to the specified value; or, the distribution of the data set is not symmetric about the default value"),
HTML("m < m&#8320: the population median of X is less than the specified value"),
HTML("m > m&#8320: the population median of X is greater than the specified value")),
choiceValues = list("two.sided", "less", "greater")),

helpText("Correction"),
radioButtons("nap.wsr", label = "Normal Approximation", 
choices = list("Sample size is not large" = FALSE,
   "Sample size is moderate large" = TRUE, 
   "Small sample size" = TRUE), selected = FALSE),
helpText("Normal approximation is applicable when sample size > 10.")),

mainPanel(
h4('Results of Wilcoxon Signed-Rank Test'), 
tableOutput("ws.test"), 
helpText("When normal approximation is applied, the name of test becomes 'Wilcoxon signed rank test with continuity correction'")
)
)
}
##---------- data ----------
##' @title UI of One Sample (Non-paramatric Tests)
##' @export
nptest.onesample <- function(){

sidebarLayout(  

sidebarPanel(

h4("Data Preparation"),

tabsetPanel(
##-------input data-------## 
tabPanel("Manual input", p(br()),
helpText("Missing value is input as NA"),

tags$textarea(id="a", rows=10, "1.8\n3.3\n6.7\n1.4\n2.2\n1.6\n13.6\n2.8\n1.0\n2.8\n6.5\n6.8\n0.7\n0.9\n3.4\n3.3\n1.4\n0.9\n1.4\n1.8"),
helpText("Change the names of the samples (optional)"), 
tags$textarea(id="cn", rows=2, "X")
),

##-------csv file-------##   
tabPanel("Upload CSV file", p(br()),
fileInput('file', 'Choose CSV file', 
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv')),
checkboxInput('header', 'Header', TRUE), #p
radioButtons('sep', 'Separator', c(Comma=',', Semicolon=';', Tab='\t'), ',')) 
),

hr(),
h4("Configuration"),
numericInput("med", HTML("The specific value, m&#8320"), 4)#p),
),

mainPanel(

h4("Descriptive Statistics"),

tabsetPanel(

tabPanel("Data Display", p(br()),  

dataTableOutput("table")),

tabPanel("Basic descriptives", p(br()), 

splitLayout(
tableOutput("bas"), 
tableOutput("des"), 
tableOutput("nor"))  ),

tabPanel("Boxplot", p(br()), 

splitLayout(
plotOutput("bp", width = "400px", height = "400px", click = "plot_click"),

wellPanel(
verbatimTextOutput("info"), hr(),

helpText(
HTML(
"Notes:
<ul>
<li> Points are simulated and located randomly in the same horizontal line 
<li> Outliers will be highlighted in red, if existing
<li> The red outlier may not cover the simulated point
<li> The red outlier only indicates the value in horizontal line
</ul>"
)
)
)
) 
),

tabPanel("Histogram", p(br()), 

plotOutput("makeplot", width = "800px", height = "400px"),
sliderInput("bin", "The width of bins in histogram", min = 0.01, max = 5, value = 0.2)
)
)
)
)
}