我正在运行一个函数，用于对 Dataframe 的不同子集进行多个加权t检验。我的功能基本上如下：

library(weights)

group_list <- list(unique(df$group))

t_tests <- for (g in group_list){wtd.t.test(x=df[df$group == g,]$var2[df[df$group == g,]$var1=="A"],y=df[df$group == g,]$var2[df[df$group == g,]$var1=="B"],
weight=df[df$group == g,]$weight[df[df$group == g,]$var1=="A"],weighty=df[df$group == g,]$weight[df[df$group == g,]$var1=="B"],samedata=FALSE)}

其中，var2是关注的结果变量。我想测试var1 =“A”和var1 =“B”的均值之间差异的显著性，并对变量group的不同值的每个数据子集执行此操作。
我使用了上面的代码，但错误是Error in wtd.t.test(x = df[df$group == g, : object 'out' not found我的函数结构不正确吗？我如何对 Dataframe 的每个子集进行加权t测试？

更新：建议使用嵌套tibles的新方法

我的新方法如下：

library(weights)
library(tidyverse)

df %>% 
  nest(-group) %>% 
  mutate(fit = map(data, ~ wtd.t.test(x=.%>%filter(var1 == "A")$var2,y=.%>% filter(var1 == "B")$var2,
weight=.%>% filter(var1 == "A")$weight,weighty=.%>% filter(var1 == "B")$weight,samedata=FALSE)),
         results = map(fit, glance)) %>% 
  unnest(results)

新的错误消息为：

Error in `mutate()`:
ℹ In argument: `fit = map(...)`.
Caused by error in `map()`:
ℹ In index: 1.
Caused by error in `weight / mean(weight, na.rm = TRUE)`:
! non-numeric argument to binary operator
Backtrace:
  1. ... %>% unnest(results)
 10. purrr::map(...)
 11. purrr:::map_("list", .x, .f, ..., .progress = .progress)
 15. .f(.x[[i]], ...)
 16. weights::wtd.t.test(...)

我所有的变量都是数字，除了Var1，它不用于计算，所以我不清楚为什么会出现这个错误消息。任何建议将不胜感激。
如果我重新格式化代码如下：

df %>% 
  nest(-country) %>% 
  mutate(fit = map(data, ~ wtd.t.test(x=filter(.,var1 == "A")$var2,y=filter(.,var1 == "B")$var2,
weight=filter(.,var1 == "A")$weight,weighty=filter(.,var1 == "B")$weight,samedata=FALSE)),
         results = map(fit, glance)) %>% 
  unnest(results)

现在错误变为：

Error in `mutate()`:
ℹ In argument: `fit = map(...)`.
Caused by error in `map()`:
ℹ In index: 1.
Caused by error in `wtd.t.test()`:
! object 'out' not found
Backtrace:
  1. ... %>% unnest(results)
 10. purrr::map(...)
 11. purrr:::map_("list", .x, .f, ..., .progress = .progress)
 15. .f(.x[[i]], ...)
 16. weights::wtd.t.test(...)

更新2

下面是使用可复制示例更新的新代码：

library(weights)
library(tidyverse)

mtcars %>% 
  nest(-cyl) %>% 
  mutate(fit = map(data, ~ wtd.t.test(x=.%>%filter(gear == 3)$disp,y=.%>% filter(gear = 4)$disp,
weight=.%>% filter(gear == 3)$wt,weighty=.%>% filter(gear == 4)$wt,samedata=FALSE)),
         results = map(fit, glance)) %>% 
  unnest(results)

并重新格式化：

mtcars %>% 
  nest(-cyl) %>% 
  mutate(fit = map(data, ~ wtd.t.test(x=filter(.,gear == 3)$disp,y=filter(.,gear == 4)$disp,
weight=filter(.,gear == 3)$weight,weighty=filter(.,gear == 4)$weight,samedata=FALSE)),
         results = map(fit, glance)) %>% 
  unnest(results)