R:Dplyr'；分组人'；在有光泽的环境中似乎不起作用

我刚刚开始使用Shiny进行实验，但我在让dplyr的“groupby”函数工作时遇到了一个问题

我的总体想法是，我有一个数据集，其中包含许多数字变量和一个变量，通过这些变量可以对这些变量进行分组（在我的例子中是19个国家，因此变量范围为1到19）。 现在我想使用metafor软件包对每个国家的两个变量之间的相关性进行荟萃分析。 因此，我想分别计算每个国家的两个选定变量之间的相关性，然后将它们放在一个荟萃分析中，最后显示这些影响的森林图

我以mtcars数据集为例，说明我已经取得了多大的进步：

UI：

library(shiny)
library(metafor)
library(dplyr)


ui <- fluidPage(
  sidebarPanel(

    selectInput("x", label = "Choose Variable I", 
    choices = c("Displacement (cu.in.)", "Horsepower", "Rear axle ratio",
    "Weight (1000lbs)", "1/4 mile time"), selected = "Displacement (cu.in.)"),

    selectInput("y", label = "Choose Variable II", 
    choices = c("Displacement (cu.in.)", "Horsepower", "Rear axle ratio",
    "Weight (1000lbs)", "1/4 mile time"), selected = "Horsepower")
  ),

  mainPanel(
    plotOutput(outputId = "plot")
    ) 
  )

 server <- function(input, output) {


  output$plot <-renderPlot({

    data_x <- switch(input$x, 
                     "Displacement (cu.in.)" = mtcars$disp,
                     "Horsepower" = mtcars$hp,
                     "Rear axle ratio" = mtcars$drat,
                     "Weight (1000lbs)" = mtcars$wt,
                     "1/4 mile time" = mtcars$qsec)

    data_y <- switch(input$y, 
                     "Displacement (cu.in.)" = mtcars$disp,
                     "Horsepower" = mtcars$hp,
                     "Rear axle ratio" = mtcars$drat,
                     "Weight (1000lbs)" = mtcars$wt,
                     "1/4 mile time" = mtcars$qsec)

    meta_main <- mtcars %>% 
      group_by(gear) %>% 
      summarise(participantID = n(), 
                correlation = cor(data_x, data_y, use = "complete.obs"))


    meta <- rma(ni=participantID, ri=correlation, 
                method="REML", measure="COR", data=meta_main)


    forest(meta) 

  })

}

shinyApp(ui = ui, server = server)

库（闪亮）
图书馆（metafor）
图书馆（dplyr）
ui试试这个服务器功能，首先你应该加载
lazyeval
包

server <- function(input, output) {

output$plot <-renderPlot({

data_x <- switch(input$x, 
                 "Displacement (cu.in.)" = "disp",
                 "Horsepower" = "hp",
                 "Rear axle ratio" = "drat",
                 "Weight (1000lbs)" = "wt",
                 "1/4 mile time" = "qsec")

data_y <- switch(input$y, 
                 "Displacement (cu.in.)" = "disp",
                 "Horsepower" = "hp",
                 "Rear axle ratio" = "drat",
                 "Weight (1000lbs)" = "wt",
                 "1/4 mile time" = "qsec")

meta_main <- mtcars %>% 
  group_by(gear) %>% 
  mutate(participantID = n()) %>%
  group_by(gear, participantID) %>% 
  summarise_(correlation = interp(~cor(x, y, use = "complete.obs"), x = as.name(data_x), y = as.name(data_y)))


meta <- rma(ni=participantID, ri=correlation, 
            method="REML", measure="COR", data=meta_main)


forest(meta) 

})

}

server当您尝试按组分组时，您是否也使用了
summary\uu
！这很有效。非常感谢你，我已经试了很久了！我需要看看标准评估方法。注意这些方法现在已经过时了。