McNemar Test — ifr_mcnemar_test • inferr

Test if the proportions of two dichotomous variables are equal in the same population.

Usage

ifr_mcnemar_test(data, x = NULL, y = NULL)

Arguments

data: a data.frame or tibble
x: factor; column in data
y: factor; column in data

Value

ifr_mcnemar_test returns an object of class "ifr_mcnemar_test". An object of class "ifr_mcnemar_test" is a list containing the following components:

statistic: chi square statistic
df: degrees of freedom
pvalue: p-value
exactp: exact p-value
cstat: continuity correction chi square statistic
cpvalue: continuity correction p-value
kappa: kappa coefficient; measure of interrater agreement
std_err: asymptotic standard error
kappa_cil: 95% kappa lower confidence limit
kappa_ciu: 95% kappa upper confidence limit
cases: cases
controls: controls
ratio: ratio of proportion with factor
odratio: odds ratio
tbl: two way table

Deprecated Function

infer_mcnermar_test() has been deprecated. Instead use ifr_mcnemar_test().

References

Sheskin, D. J. 2007. Handbook of Parametric and Nonparametric Statistical Procedures, 4th edition. : Chapman & Hall/CRC.

See also

Examples

# using variables from data
hb <- hsb
hb$himath <- ifelse(hsb$math > 60, 1, 0)
hb$hiread <- ifelse(hsb$read > 60, 1, 0)
ifr_mcnemar_test(hb, himath, hiread)
#>            Controls 
#> ---------------------------------
#> Cases       0       1       Total 
#> ---------------------------------
#>   0        135      21        156 
#>   1         18      26         44 
#> ---------------------------------
#> Total      153      47        200 
#> ---------------------------------
#> 
#>        McNemar's Test        
#> ----------------------------
#> McNemar's chi2        0.2308 
#> DF                         1 
#> Pr > chi2              0.631 
#> Exact Pr >= chi2      0.7493 
#> ----------------------------
#> 
#>        Kappa Coefficient         
#> --------------------------------
#> Kappa                     0.4454 
#> ASE                        0.075 
#> 95% Lower Conf Limit      0.2984 
#> 95% Upper Conf Limit      0.5923 
#> --------------------------------
#> 
#> Proportion With Factor 
#> ----------------------
#> cases             0.78 
#> controls         0.765 
#> ratio           1.0196 
#> odds ratio      1.1667 
#> ----------------------

# test if the proportion of students in himath and hiread group is same
himath <- ifelse(hsb$math > 60, 1, 0)
hiread <- ifelse(hsb$read > 60, 1, 0)
ifr_mcnemar_test(table(himath, hiread))
#>            Controls 
#> ---------------------------------
#> Cases       0       1       Total 
#> ---------------------------------
#>   0        135      21        156 
#>   1         18      26         44 
#> ---------------------------------
#> Total      153      47        200 
#> ---------------------------------
#> 
#>        McNemar's Test        
#> ----------------------------
#> McNemar's chi2        0.2308 
#> DF                         1 
#> Pr > chi2              0.631 
#> Exact Pr >= chi2      0.7493 
#> ----------------------------
#> 
#>        Kappa Coefficient         
#> --------------------------------
#> Kappa                     0.4454 
#> ASE                        0.075 
#> 95% Lower Conf Limit      0.2984 
#> 95% Upper Conf Limit      0.5923 
#> --------------------------------
#> 
#> Proportion With Factor 
#> ----------------------
#> cases             0.78 
#> controls         0.765 
#> ratio           1.0196 
#> odds ratio      1.1667 
#> ----------------------

# using matrix
ifr_mcnemar_test(matrix(c(135, 18, 21, 26), nrow = 2))
#>            Controls 
#> ---------------------------------
#> Cases       0       1       Total 
#> ---------------------------------
#>   0        135      21        156 
#>   1         18      26         44 
#> ---------------------------------
#> Total      153      47        200 
#> ---------------------------------
#> 
#>        McNemar's Test        
#> ----------------------------
#> McNemar's chi2        0.2308 
#> DF                         1 
#> Pr > chi2              0.631 
#> Exact Pr >= chi2      0.7493 
#> ----------------------------
#> 
#>        Kappa Coefficient         
#> --------------------------------
#> Kappa                     0.4454 
#> ASE                        0.075 
#> 95% Lower Conf Limit      0.2984 
#> 95% Upper Conf Limit      0.5923 
#> --------------------------------
#> 
#> Proportion With Factor 
#> ----------------------
#> cases             0.78 
#> controls         0.765 
#> ratio           1.0196 
#> odds ratio      1.1667 
#> ----------------------