需要帮助在R中对CSV文档的不同列执行自动未配对t检验。

Question

我想在第2列和第3栏、第4栏和第5栏、第6栏和第7栏之间进行自动配对t检验。当我使用下面的代码时，我可以执行t检验，但不能执行未配对的t检验。

数据：

 patient weight_1 weight_2    BMI_1    BMI_2 chol_1 chol_2    gly_1    gly_2
1       A     86.0     97.0 34.44961 30.61482   86.0   97.0 34.44961 30.61482
2       B    111.0     55.5 33.51045 22.80572  111.0   55.5 33.51045 22.80572
3       C     92.4     70.0 28.51852 25.71166   92.4   70.0 28.51852 25.71166

代码：

names <- colnames(dataframe)
 for(i in seq(from = 2, to = 8, by = 2)){
 print(names[i])
 print(names[i+1]) 
 print(t.test(dataframe[i], dataframe[i+1]))
 }

产出：

1 "weight_1“1 "weight_2”

        Welch Two Sample t-test

data:  dataframe[i] and dataframe[i + 1]
t = 1.3183, df = 75.892, p-value = 0.1914
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -2.459965 12.090735
sample estimates:
mean of x mean of y 
 91.50256  86.68718 
[1] "BMI_1"
[1] "BMI_2"

        Welch Two Sample t-test

data:  dataframe[i] and dataframe[i + 1]
t = 1.5851, df = 75.866, p-value = 0.1171
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -0.3817027  3.3571650
sample estimates:
mean of x mean of y 
 30.45167  28.96394 

诸若此类。当我将paired=TRUE添加到数据时：

 names <- colnames(dataframe)
 for(i in seq(from = 2, to = 8, by = 2)){
 print(names[i])
 print(names[i+1]) 
 print(t.test(dataframe[i], dataframe[i+1]), paired=TRUE)
 }

结果是完全相同的，好像它不包括配对函数。有人能帮我吗？在此之前，非常感谢您。

Answer 1

您必须更改t.test中的索引，以清楚地定义要使用以下列：

例如：

df <- data.frame(a = runif(10), b=runif(10), c=runif(10))
    
    t1 <- t.test(df[1], df[2])
    t1$p.value
    
    t2 <- t.test(df[1], df[2], paired=T)
    t2$p.value
Error in `[.data.frame`(y, yok) : undefined columns selected

但

t2 <- t.test(df[,1], df[,2], paired=T)
t2$p.value

很管用。所以在你的代码中应该是

print(t.test(dataframe[,i], dataframe[,i+1], paired=TRUE)) 

对于配对的t.test。

我建议在配对t检验中也使用这种形式的索引，尽管它不会抛出任何错误。