CODEWITHSUNDEEP
rchi-squared
Scott Davis
Scott Davis

Reputation: 993

error creating chisq.test() in R - invalid 'type' (character) of argument

I am creating a chi-squared test for independence on a data.frame called Comp1 with two binary variables and 13109 obs.

I am using the test before clustering consumers based on demographics. If the two variables are dependent on one another, then certain values will be in a cluster. The two variables are a subset from another data.frame with 36 variables.

I got an error saying the data.frame had character variables instead of factors that the str() function shows.

Why does the error say the data.frame has character values?

data:

> str(Comp1)
'data.frame':   13109 obs. of  2 variables:
 $ HomeOwnerStatus: Factor w/ 2 levels "Own","Rent": 1 2 2 2 1 2 1 1 2 2 ...
 $ MaritalStatus  : Factor w/ 2 levels "Married","Single": 2 1 1 1 2 1 2 1 1 1 ...

example:

> #Create dataset
> homeownerstatus <- c("Own", "Rent", "Own", "Own", "Rent", "Own")
> maritalstatus <- c("Married", "Married", "Married", "Single", "Single", "Married")
> Comp1 <- data.frame(homeownerstatus, maritalstatus)

error with solution:

> #Test binary variables for independence 
> #Create matrix from data.frame
> DF4 <- as.matrix(Comp1)
> #Comparison of marital status and home owner status
> #Perform chi-squared test for independence of two variables
> chisq.test(table(Comp1))

    Chi-squared test for given probabilities

data:  table(DF4)
X-squared = 295149.5, df = 71, p-value < 2.2e-16

Upvotes: 1

Views: 11290

Answers (1)

BenBarnes
BenBarnes

Reputation: 19454

chisq.test either wants a factor vector for both its x and y arguments or a matrix or data.frame for the x argument. When a data.frame is passed, this gets converted to a matrix by the function as.matrix. This step coerces the factor columns in your data.frame to character.

> as.matrix(Comp1)
     homeownerstatus maritalstatus
[1,] "Own"           "Married"    
[2,] "Rent"          "Married"    
[3,] "Own"           "Married"    
[4,] "Own"           "Single"     
[5,] "Rent"          "Single"     
[6,] "Own"           "Married"

So, my suggestion would be to pass two factor vectors:

chisq.test(Comp1$homeownerstatus, Comp1$maritalstatus)

        Pearson's Chi-squared test with Yates' continuity correction

data:  Comp1$homeownerstatus and Comp1$maritalstatus
X-squared = 0, df = 1, p-value = 1

Warning message:
In chisq.test(Comp1$homeownerstatus, Comp1$maritalstatus) :
  Chi-squared approximation may be incorrect

EDIT

When you pass a matrix or a data.frame to the x argument, that object is taken to be a contingency table, which is not what you want here. You have two binary variables whose contingency table should be calculated and then tested according to the chi-squared test. Therefore you should pass each factor vector as described above or, alternatively, calculate the contingency table and pass that to chisq.test.

chisq.test(table(Comp1))

Upvotes: 1

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