我正在尝试构建一个样本量计算器并且我一直收到错误
$ operator is invalid for atomic vectors
我已尝试过所有内容，但此错误仍然存在。用户输入一些值，闪亮的反应性获取值，检查用户想要计算的值并返回结果。可能有什么不对？我的代码如下：
#options(shiny.trace = TRUE)
#check for and/or install dependencies
need<-c("shiny","ggplot2","pwr","googleVis") # some more should auto load...
for(i in 1:length(need)){
if(require(need[i], character.only = TRUE)==FALSE){install.packages(need[i]);library(need[i], character.only = TRUE)} else { library(need[i],character.only = TRUE)}
}
library(googleVis)
library(shiny)
library(ggplot2)
library(pwr)
# load code for custom functions
source("plot.R") # for using ggplot
#data <- read.csv("dataset.csv",headers=T)
calculationTypes <-c("default","2p.test","2p2n.test",
"anova.test","chisq.test", "f2.test",
"p.test","r.test","t.test","t2n.test")
names(calculationTypes) <- c("Select Function Type",
"Proportions (equal n)",
"Two proportions (unequal n)",
"Balanced one way ANOVA",
"Chi-square test",
"General linear model",
"Proportion (one sample)",
"Correlation",
"T-tests (one sample, 2 sample, paired)",
"T-test (two samples with unequal n)")
valueCalculate <-c("sampleSize","alternateSampleSize","effectSize","significanceLevel","samplePower", "correlation")
names(valueCalculate) <- c("Sample Size","Second Sample Size","Effect Size","Significance Level","Power","Correlation")
customHeaderPanel <- function(title,windowTitle=title){
tagList(
tags$head(
tags$title(windowTitle),
tags$link(rel="stylesheet", type="text/css",href="app.css")
),
HTML("<div class='row-fluid'>"),
HTML("<div class='span9'>"),
HTML("<div class='row-fluid' id='header'>"),
div(class = "span3",imageOutput("logo", height = "153px", width="272px")),
div(class = "span6",h1(title)),
HTML("</div>"),
HTML("</div>"),
HTML("</div>")
)
}
shinyServer(function(input, output, session) {
sigLevel <- NULL
pwr <- NULL
sample <- NULL
altSample <- NULL
effSize <- NULL
observe({
if(input$calculate == 0){ #check if this is first run
return()
}
isolate({
# Read inputs and save values to database here
})
})
#KEMRI wellcome Trust programme logo
output$logo <- renderImage({
filename <- 'logo.png'
list(src = filename,
contentType = 'image/png',
width = 272,
height = 153,
alt = "KEMRI-Wellcome Trust Programme")
}, deleteFile = FALSE)
#Capture user input for calculating the sample size
sampleSize <- reactive ({ as.numeric(input$sampleSize) })
alternateSampleSize <- reactive ({ input$alternateSampleSize }) # conditional for t2n.test
effectSize <- reactive ({ as.numeric(input$effectSize) })
significanceLevel <- reactive ({ as.numeric(input$significanceLevel) })
degFreedom <- reactive ({ as.numeric(input$degFreedom) })
numerator <- reactive ({ as.numeric(input$numerator) })
denominator <- reactive ({ as.numeric(input$denominator) })
samplePower <- reactive ({ as.numeric(input$samplePower) })
groupCount <- reactive ({ if(is.na(input$groupCount))
NULL
else
as.numeric(input$groupCount)
}) #conditional for annova
ttestType <- reactive ({ input$ttestType })
correlation <- reactive ({ as.numeric(input$correlation) }) #should be between 0 and 1
valueToCalculate <- reactive ({ input$valueToCalculate })
# Return the requested calculation
powerAnalysisFunction <- reactive({ input$powerAnalysisFunction })
output$calculatedSampleSize <- renderUI({
sigLevel <- significanceLevel()
pwr <- samplePower()
sample <- sampleSize()
altSample <- alternateSampleSize()
effSize <- effectSize()
calcVal <- valueToCalculate()
linearRegDenom <- denominator()
linearRegNum <- numerator()
freedomDegrees <- degFreedom()
if(calcVal=='sampleSize')
sample <- NULL
else if(calcVal =='alternateSampleSize')
altSample <- NULL
else if(calcVal =='effectSize')
effSize <- NULL
else if(calcVal =='significanceLevel')
sigLevel <- NULL
else if(calcVal =='samplePower')
pwr <- NULL
if(powerAnalysisFunction() =='2p.test'){ #two proportions (equal n)
print(pwr.2p.test(h =effSize , n =sample , sig.level = sigLevel, power = pwr ))
}else if(powerAnalysisFunction() =='2p2n.test'){ #two proportions (unequal n)
print(pwr.2p2n.test(h =effSize , n1 =sample , n2 =altSample , sig.level =sigLevel , power =pwr ))
}else if(powerAnalysisFunction() == 'anova.test'){ #balanced one way ANOVA
print(pwr.anova.test(k = groupCount(), n = sample, f = effSize, sig.level = sigLevel, power=pwr ))
}else if(powerAnalysisFunction() == 'chisq.test'){ #chi-square test
print(pwr.chisq.test(w =effSize, N =sample , df =freedomDegrees , sig.level =sigLevel, power =pwr ))
}else if(powerAnalysisFunction() == 'f2.test'){ #general linear model
print(pwr.f2.test(u = linearRegNum, v = linearRegDenom, f2 =effSize , sig.level = sigLevel , power =pwr ))
}else if(powerAnalysisFunction() == 'p.test'){ #proportion (one sample)
print(pwr.p.test(h = effSize, n =sample , sig.level =sigLevel, power = pwr ))
}else if(powerAnalysisFunction() == 'r.test'){ #correlation
print(pwr.r.test(n = sample, r = correlation(), sig.level = sigLevel, power = pwr ))
}else if(powerAnalysisFunction() == 't.test'){ #t-tests (one sample, 2 sample, paired)
print(pwr.t.test(n = sample , d = effSize , sig.level = sigLevel , power = pwr , type = c("two.sample", "one.sample", "paired")))
}else if(powerAnalysisFunction() == 't2n.test'){ #t-test (two samples with unequal n)
print(pwr.t2n.test(n1 = sample , n2= altSample , d = effSize , sig.level = sigLevel, power = pwr ))
}
})
})
# Define UI for application that plots random distributions
shinyUI(pageWithSidebar(
# Application title
customHeaderPanel("KEMRI Wellcome Trust Programme"),
# Sidebar with a slider input for number of observations
sidebarPanel(
selectInput("powerAnalysisFunction","Power Calculations For",
choices = calculationTypes),
sliderInput("sampleSize", "Sample Size:",
min=0, max=1000, value=20),
sliderInput("alternateSampleSize", "Second Sample Size:",
min=0, max=1000, value=20),
sliderInput("effectSize", "Effect Size:",
min=0, max=1, value=0.80, step = 0.05),
sliderInput("significanceLevel", "Significance Level:",
min=0, max=1, value=0.05, step = 0.05),
sliderInput("samplePower", "Power:",
min=0, max=1, value=0.5, step = 0.05),
sliderInput("correlation", "Correlation:",
min=0, max=1, value=0.5, step = 0.05),
sliderInput("degFreedom", "Chi-square:Degrees of freedom",
min=0, max=10, value=5, step = 1),
sliderInput("numerator", "Linear Model:Numerator(Degrees of freedom):",
min=0, max=1, value=0.5, step = 0.05),
sliderInput("denominator", "Linear Model:Denominator(Degrees of freedom):",
min=0, max=1, value=0.5, step = 0.05),
numericInput("groupCount", "Group Count (For Annova)",2),
selectInput("valueToCalculate","Value to calculate",
choices = valueCalculate),
br(),
actionButton("calculate", "Calculate")
),
mainPanel(
tabsetPanel(id = "tabs",
tabPanel(id="sampleSize","Sample Size Calc",htmlOutput("calculatedSampleSize"))
)
)
))#End of UI
这段代码可能有什么问题？提到哪些原子载体？如何纠正此错误？
答案 0 :(得分：1)
问题在于反应式renderUI功能。计算结果属于power.htest类。为了解决这个错误，我在server.R
中做了以下更改output$calculatedSampleSize <- renderUI({
results <- NULL
sigLevel <- significanceLevel()
pwr <- samplePower()
sample <- sampleSize()
altSample <- alternateSampleSize()
effSize <- effectSize()
calcVal <- valueToCalculate()
linearRegDenom <- denominator()
linearRegNum <- numerator()
freedomDegrees <- degFreedom()
if(calcVal=='sampleSize')
sample <- NULL
else if(calcVal =='alternateSampleSize')
altSample <- NULL
else if(calcVal =='effectSize')
effSize <- NULL
else if(calcVal =='significanceLevel')
sigLevel <- NULL
else if(calcVal =='samplePower')
pwr <- NULL
if(powerAnalysisFunction() =='2p.test'){ #two proportions (equal n)
results <- pwr.2p.test(h =effSize , n =sample , sig.level = sigLevel, power = pwr )
}else if(powerAnalysisFunction() =='2p2n.test'){ #two proportions (unequal n)
results <- pwr.2p2n.test(h =effSize , n1 =sample , n2 =altSample , sig.level =sigLevel , power =pwr )
}else if(powerAnalysisFunction() == 'anova.test'){ #balanced one way ANOVA
results <- pwr.anova.test(k = groupCount(), n = sample, f = effSize, sig.level = sigLevel, power=pwr )
}else if(powerAnalysisFunction() == 'chisq.test'){ #chi-square test
results <- pwr.chisq.test(w =effSize, N =sample , df =freedomDegrees , sig.level =sigLevel, power =pwr )
}else if(powerAnalysisFunction() == 'f2.test'){ #general linear model
results <- pwr.f2.test(u = linearRegNum, v = linearRegDenom, f2 =effSize , sig.level = sigLevel , power =pwr )
}else if(powerAnalysisFunction() == 'p.test'){ #proportion (one sample)
results <- pwr.p.test(h = effSize, n =sample , sig.level =sigLevel, power = pwr )
}else if(powerAnalysisFunction() == 'r.test'){ #correlation
results <- pwr.r.test(n = sample, r = correlation(), sig.level = sigLevel, power = pwr )
}else if(powerAnalysisFunction() == 't.test'){ #t-tests (one sample, 2 sample, paired)
results <- pwr.t.test(n = sample , d = effSize , sig.level = sigLevel , power = pwr , type = c("two.sample", "one.sample", "paired"))
}else if(powerAnalysisFunction() == 't2n.test'){ #t-test (two samples with unequal n)
results <- pwr.t2n.test(n1 = sample , n2= altSample , d = effSize , sig.level = sigLevel, power = pwr )
}else{
results <- " "
}
return(tags$div(results))
})
答案 1 :(得分：0)
ui.R
ttestType <- reactive ({ input$ttestType })