Question

我一直在R中做一个样本t检验，但是今天我遇到了一个很大的挑战。我将数据按一个变量分组，我想对每个组执行一个样本t检验。我可以在SPSS中完美地做到这一点，但现在R令人头疼，无论谁知道如何做到这一点都可以。

Location=rep(c("Area_A","Area_B"),4) 
temp=rnorm(length(Location),34,5) 
sample_data=data.frame(Location,ph)
sample_data
Location       temp
1   Area_A 32.73782
2   Area_B 26.29996
3   Area_A 40.75101
4   Area_B 26.68309
5   Area_A 33.94259
6   Area_B 26.48326
7   Area_A 37.92506
8   Area_B 29.22532

假设上例中的假设均值为35，则t检验为一个样本，

t.test(sample_data$temp,mu=35)

这给了我

 One Sample t-test

data:  sample_data$ph
t = -1.6578, df = 7, p-value = 0.1413
alternative hypothesis: true mean is not equal to 35
95 percent confidence interval:
 27.12898 36.38304
sample estimates:
mean of x 
 31.75601

但这是针对所有合并的组的。我可以在SPSS中做到。有什么办法可以在R中用一行代码来完成此操作，或者如果不可能用一行代码来执行此操作，谁可以为我执行此操作。预先感谢。

Answer 1

一种解决方案是将每个组的t.test结果保存为列表：

# reproducible results
set.seed(8)

# example data
Location=rep(c("Area_A","Area_B"),4) 
temp=rnorm(length(Location),34,5) 
sample_data=data.frame(Location,temp)

library(dplyr)

dt_res = sample_data %>%
  group_by(Location) %>%                       # for each group
  summarise(res = list(t.test(temp, mu=35)))   # run t.test and save results as a list

# see the list of results
dt_res$res  

# [[1]]
# 
# One Sample t-test
# 
# data:  temp
# t = -0.76098, df = 3, p-value = 0.502
# alternative hypothesis: true mean is not equal to 35
# 95 percent confidence interval:
#   29.93251 38.11170
# sample estimates:
#   mean of x 
# 34.0221 
# 
# 
# [[2]]
# 
# One Sample t-test
# 
# data:  temp
# t = -1.045, df = 3, p-value = 0.3728
# alternative hypothesis: true mean is not equal to 35
# 95 percent confidence interval:
#   26.37007 39.36331
# sample estimates:
#   mean of x 
# 32.86669

另一种解决方案是将每个组的t.test结果保存为数据框：

library(dplyr)
library(tidyr)
library(broom)

sample_data %>%
  group_by(Location) %>%                       
  summarise(res = list(tidy(t.test(temp, mu=35)))) %>%
  unnest()

# # A tibble: 2 x 9
#   Location estimate statistic p.value parameter conf.low conf.high method            alternative
#    <fct>       <dbl>     <dbl>   <dbl>     <dbl>    <dbl>     <dbl> <chr>             <chr>      
# 1 Area_A       34.0    -0.761   0.502         3     29.9      38.1 One Sample t-test two.sided  
# 2 Area_B       32.9    -1.05    0.373         3     26.4      39.4 One Sample t-test two.sided

两种方法的原理是相同的。您按Location分组，然后对每个组进行t.test。这完全取决于您希望拥有哪种输出。

组内一个样本T-TEST IN R

1 个答案: