Creates a chi.squared test table for multiple dependent variables

Creates a chi.squared test table for multiple dependent variables

nice_chi_test_table(
  dv,
  iv,
  data,
  conditions = levels(factor(iv))[1:2],
  ref_levels = 2,
  labels = NULL,
  nice_p = TRUE,
  digits = 2,
  order = "12",
  label_attr = TRUE,
  type = "html",
  ...
)

chi_test_table(...)

Arguments

dv

A data frame with the dependent variables or a character vector when argument data is set.

iv

A data frame or vector with the independent variable or a character if argument data is set.

data

A data frame.

conditions

A character vector of length two with the names of the two conditions. Defaults to the first two levels of the independent variable 'iv' if applicable.

ref_levels

Vector with the reference level for each dependent variable. Values are repeated if length of levels vector is smaller than number dependent variables.

labels

A character vector of length two with labels for the dependent variables.

nice_p

If TRUE, p values are printed in a nice format.

digits

Number of digits for rounding mean and sd values

order

Either "12" or "21" depicting whether group two is compared to group one or vice versa.

type

Either "df" for data frame or "html" for html table.

...

Further arguments passed to nice_table()

Value

A tibble or an html table

Examples

dat <- data.frame(
  gender = factor(rbinom(100, 1, 0.3), labels = c("male", "female")),
  glasses = factor(rbinom(100, 1, 0.3), labels = c("no", "yes")),
  sen = factor(rbinom(100, 1, 0.5), labels = c("no_sen", "sen"))
 )
chi_test_table(
  c("gender", "glasses"), "sen", data = dat, 
  ref_levels = c("male", "no")
)


  
Table
Chi-squared test
    
Variable
      
Level
      

        
Proportion
      
      
X²(1)
      
p
      

        
n
      
    
no_sen
      
sen
      
Difference
      
no_sen 
      
sen 
    
gender
male
0.74
0.68
0.06
0.19
.659
50
50
glasses
no
0.78
0.72
0.06
0.21
.644
50
50
 Note. One degree of freedom for all tests.