CODEWITHSUNDEEP
r
Seyma Kalay
Seyma Kalay

Reputation: 2861

finding chi stats using function in R

I am trying to create a function to avoid retyping but It is not working, any help would be appreciated, 

library(descr)

mtcars$carb <- factor(mtcars$carb)
mtcars$gear <- factor(mtcars$gear)
CrossTable(mtcars$carb, mtcars$gear, expected=F, prop.r=T, prop.c=T, prop.t=T, prop.chisq=F, chisq = T)

My attempt so far:

a <- function(df,vec1,vec2){CrossTable(df$vec1, df$vec2, expected=F, prop.r=T, prop.c=T, prop.t=T, prop.chisq=F, chisq = T)}

a(mtcars,carb,gear)

Upvotes: 1

Views: 22

Answers (1)

linog
linog

Reputation: 6226

Putting unquoted arguments requires to use non-standard evaluation. This is not the easiest thing to do in R. I recommend you to favor arguments as column names

a <- function(df,col1,col2){CrossTable(df[,col1], df[,col2], expected=F, prop.r=T, prop.c=T, prop.t=T, prop.chisq=F, chisq = T)}

And your call will be

a(mtcars,"carb","gear")


   Cell Contents 
|-------------------------|
|                       N | 
|           N / Row Total | 
|           N / Col Total | 
|         N / Table Total | 
|-------------------------|

===========================================
              df[, col2]
df[, col1]        3       4       5   Total
-------------------------------------------
1                 3       4       0       7
              0.429   0.571   0.000   0.219
              0.200   0.333   0.000        
              0.094   0.125   0.000        
-------------------------------------------
2                 4       4       2      10
              0.400   0.400   0.200   0.312
              0.267   0.333   0.400        
              0.125   0.125   0.062        
-------------------------------------------
3                 3       0       0       3
              1.000   0.000   0.000   0.094
              0.200   0.000   0.000        
              0.094   0.000   0.000        
-------------------------------------------
4                 5       4       1      10
              0.500   0.400   0.100   0.312
              0.333   0.333   0.200        
              0.156   0.125   0.031        
-------------------------------------------
6                 0       0       1       1
              0.000   0.000   1.000   0.031
              0.000   0.000   0.200        
              0.000   0.000   0.031        
-------------------------------------------
8                 0       0       1       1
              0.000   0.000   1.000   0.031
              0.000   0.000   0.200        
              0.000   0.000   0.031        
-------------------------------------------
Total            15      12       5      32
              0.469   0.375   0.156        
===========================================

Statistics for All Table Factors

Pearson's Chi-squared test 
------------------------------------------------------------
Chi^2 = 16.5181      d.f. = 10      p = 0.0857 

Warning message:
In chisq.test(tab, correct = FALSE, ...) :
  Chi-squared approximation may be incorrect

Upvotes: 1

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