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.
label_attr: If TRUE, variable names are taken from a label attribute.
type: Either "df" for data frame or "html" for html table.
...: Further arguments passed to nice_table()

Value

A data.frame or an html table

Examples

set.seed(123)
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
0.65
0.77
0.12
1.14
.290
52
48
glasses
no
0.65
0.83
0.18
3.30
.070
52
48
 Note. One degree of freedom for all tests.

Variable	Level	Proportion			X²(1)	p	n
Table Chi-squared test
Variable	Level	no_sen	sen	Difference	X²(1)	p	no_sen	sen
gender	male	0.65	0.77	0.12	1.14	.290	52	48
glasses	no	0.65	0.83	0.18	3.30	.070	52	48
Note. One degree of freedom for all tests.