多元回归显着性检验

Question

我有Likert类型数据，一些4点量表和其他3点量表。例如：

variable.x <- c(5,2,4,5,3,1)
variable.y <- c(0,1,1,0,2,1)

my.data <- cbind(variable.x, variable.y)

library(psych)
polychoric(my.data)

#Call: polychoric(x = my.data)
#Polychoric correlations 
#           vrbl.x vrbl.y
#variable.x  1.00        
#variable.y -0.25   1.00 

# with tau of 
#               0     1   2    3   4
#variable.x -0.97 -0.43   0 0.43 Inf
#variable.y -0.43  0.97 Inf  Inf Inf

如何获得-0.25？

的相关性的显着性值

奇怪的是，使用polycor包会产生完全不同的结果：

library(polycor)
polychor(variable.x, variable.y, ML=TRUE, std.err=TRUE)

#Polychoric Correlation, ML est. = -0.7599 (0.2588)
#Test of bivariate normality: Chisquare = 9.088, df = 7, p = 0.2464

#  Row Thresholds
#  Threshold Std.Err.
#1   -0.9388   0.5519
#2   -0.5774   0.5040
#3   -0.1906   0.5267
#4    0.3979   0.5690


 #  Column Thresholds
 #  Threshold Std.Err.
 #1   -0.3891   0.5683
 #2    0.9692   0.5568

现在相关系数现在是-0.76，而不是-0.25。再次，我怎么能找到它的意义呢？