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

infer_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

infer_mcnemar_test returns an object of class "infer_mcnemar_test". An object of class "infer_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

mcnermar_test() has been deprecated. Instead use infer_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 library(dplyr)
#> #> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’: #> #> filter, lag
#> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union
hb <- mutate(hsb, himath = if_else(math > 60, 1, 0), hiread = if_else(read > 60, 1, 0) ) infer_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) infer_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 infer_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 #> ----------------------