To calculate polychoric correlation in R, you can use **polycor()** function from **polycor** package. The polychoric correlation measures the association between two ordinal variables by estimating the correlation between the underlying continuous variables.

The following method shows how you can do it with syntax.

**Method: Use polycor() Function**

```
library(polycor)
polychor(vector1,vector2)
```

There is value for polychoric correlation ranges from -1 to 1. -1 :-indicates a perfect negative correlation. 0:- indicates no correlation. 1:- indicates a perfect positive correlation.

The following example shows how to calculate polychoric correlation in R using **polycor()** function from **polycor** package.

## Using polycor() Function

Let’s see how we can calculate polychoric correlation using **polycor()** function.

```
# Import polycor library
library(polycor)
# Create data frames
df1 <- data.frame(Machine_name=c("A1","B1","C1","D1","E1","F1","G1","H1"),
Status=c(1,1,2,3,3,2,2,1))
df2 <- data.frame(Machine_name=c("A1","B1","C1","D1","E1","F1","G1","H1"),
Status=c(2,1,1,2,1,3,3,1))
# Calculate polychoric correlation
x <- polychor(df1$Status,df2$Status)
# Print polychoric correlation
print(x)
```

Output:

```
[1] 0.1838185
```

Here the output shows polychoric correlation between **Status** column of both data frame.