有多种方法可以做到这一点，但我正在使用 dplyr 和 broom 包的组合。此过程的优点是您可以将 t 检验信息导出为数据集：

library(dplyr)
library(broom)

set.seed(9)

# example dataset
dt = data.frame(species = c(rep("ARGAFF",6), rep("BATABY",6)),
                region = rep(c("EQ","OMZ"),6),
                N15 = rnorm(12,10,1))


dt_result = dt %>% group_by(species) %>% do(tidy(t.test(N15~region, data=.)))

dt_result

   #   species  estimate estimate1 estimate2 statistic   p.value parameter   conf.low conf.high
   # 1  ARGAFF 0.6029705  9.842659  9.239688  1.381967 0.2439265  3.732157 -0.6434982  1.849439
   # 2  BATABY 1.0238324 10.740491  9.716659  1.994738 0.1673019  2.300604 -0.9298488  2.977514

希望对你有效。

首先，通常附加数据集是个坏主意。你可以修改你的lapply陈述来做你想做的事情。

set.seed(9)

# example dataset
SIA <- data.frame(species = as.factor(c(rep("ARGAFF",6), rep("BATABY",6))),
                region = as.factor(rep(c("EQ","OMZ"),6)),
                N15 = rnorm(12,10,1))

spp <- split(SIA, SIA$species,drop=FALSE) 
out <- vector("list", length = length(spp))
out <- lapply(1:length(spp),function (x) out[[x]]<- t.test(spp[[x]]$N15 ~ spp[[x]]$region))

然后你可以提取你想要的任何特征。

> out
[[1]]

    Welch Two Sample t-test

data:  spp[[x]]$N15 by spp[[x]]$region
t = -0.7566, df = 2.4628, p-value = 0.515
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -4.617903  3.018924
sample estimates:
 mean in group EQ mean in group OMZ 
         9.982135         10.781625 


[[2]]

    Welch Two Sample t-test

data:  spp[[x]]$N15 by spp[[x]]$region
t = 0.66769, df = 3.2858, p-value = 0.5483
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -1.564611  2.448523
sample estimates:
 mean in group EQ mean in group OMZ 
        10.055578          9.613622 

Rstatix::t_test()是一个用户友好的包装器，t.test()它返回一个小标题。

library(tidyverse)
library(rstatix)

df <- tribble(~species, ~region,  ~N15,     
              "ARGAFF",    "EQ",  9.85,     
              "ARGAFF",    "EQ", 10.42,   
              "ARGAFF",    "EQ", 10.43,  
              "ARGAFF",   "OMZ", 10.28,  
              "ARGAFF",   "OMZ", 10.30,   
              "ARGAFF",   "OMZ", 10.41,  
              "BATABY",    "EQ", 10.57,      
              "BATABY",    "EQ", 10.60,      
              "BATABY",    "EQ", 10.68,        
              "BATABY",   "OMZ",  9.21,       
              "BATABY",   "OMZ",  9.29,       
              "BATABY",   "OMZ",  9.67)
df %>%
  group_by(species) %>%
  t_test(N15~region)