在R中对Spearman的相关性执行相关性测试时,如何避免出现“无法计算具有联系的精确p值”的警告?
当变量不是连续的但可以排序时,我们不使用皮尔逊相关系数来找到线性关系,在这种情况下,斯皮尔曼相关系数就出现了。由于spearman相关系数考虑了值的等级,因此相关性测试忽略了相同的等级来找到p值,结果我们得到警告“无法计算具有联系的精确p值”。可以通过在cor.test函数中使用精确= FALSE来避免这种情况。
示例
请看以下向量并执行spearman相关测试以检查它们之间的关系-
x1<-rpois(20,2)y1<-rpois(20,5)
cor.test(x1,y1,method="spearman")
输出结果
Spearman's rank correlation rhodata: x1 and y1
S = 1401.7, p-value = 0.8214
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
-0.05390585
Warning message:
In cor.test.default(x1, y1, method = "spearman") :
Cannot compute exact p-value with ties
在这里,我们有领带的警告,可以通过使用精确= FALSE来避免,如下所示-
示例
cor.test(x1,y1,method="spearman",exact=FALSE)
输出结果
Spearman's rank correlation rhodata: x1 and y1
S = 1401.7, p-value = 0.8214
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
-0.05390585
让我们看看更多示例-
示例
x2<-sample(1:100,500,replace=TRUE)y2<-sample(1:50,500,replace=TRUE)
cor.test(x2,y2,method="spearman")
输出结果
Spearman's rank correlation rhodata: x2 and y2
S = 20110148, p-value = 0.4387
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
0.03470902
Warning message:
In cor.test.default(x2, y2, method = "spearman") :
Cannot compute exact p-value with ties
示例
cor.test(x2,y2,method="spearman",exact=FALSE)
输出结果
Spearman's rank correlation rhodata: x2 and y2
S = 20110148, p-value = 0.4387
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
0.03470902
示例
x3<-sample(101:110,5000,replace=TRUE)y3<-sample(501:510,5000,replace=TRUE)
cor.test(x3,y3,method="spearman")
输出结果
Spearman's rank correlation rhodata: x3 and y3
S = 2.0642e+10, p-value = 0.5155
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
0.009199129
Warning message:
In cor.test.default(x3, y3, method = "spearman") :
Cannot compute exact p-value with ties
示例
cor.test(x3,y3,method="spearman",exact=FALSE)
输出结果
Spearman's rank correlation rhodata: x3 and y3
S = 2.0642e+10, p-value = 0.5155
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
0.009199129
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