Confidence intervals for pairwise proportion differences of a multinomial variable

Source: R/statpsych3.R

Computes adjusted Wald confidence intervals for pairwise proportion differences of a multinomial variable in a single sample. These adjusted Wald confidence intervals use the same method that is used to compare the two proportions in a paired-samples design.

ci.pairs.mult(alpha, f)

Arguments

alpha

alpha level for 1-alpha confidence

f

vector of multinomial frequency counts

Value

Returns a matrix with the number of rows equal to the number of pairwise comparisons. The columns are:

  • Estimate - adjusted estimate of proportion difference

  • SE - adjusted standard error

  • LL - lower limit of the adjusted Wald confidence interval

  • UL - upper limit of the adjusted Wald confidence interval

References

Bonett DG, Price RM (2012). “Adjusted wald confidence interval for a difference of binomial proportions based on paired data.” Journal of Educational and Behavioral Statistics, 37(4), 479--488. ISSN 1076-9986, doi:10.3102/1076998611411915 .

Examples

f <- c(125, 82, 92)
ci.pairs.mult(.05, f)
#>         Estimate         SE          LL         UL
#>  1 2  0.14285714 0.04731825  0.05011508 0.23559920
#>  1 3  0.10963455 0.04875715  0.01407230 0.20519680
#>  2 3 -0.03322259 0.04403313 -0.11952594 0.05308076

# Should return:
#        Estimate         SE          LL         UL
# 1 2  0.14285714 0.04731825  0.05011508 0.23559920
# 1 3  0.10963455 0.04875715  0.01407230 0.20519680
# 2 3 -0.03322259 0.04403313 -0.11952594 0.05308076