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Confidence interval for a paired-samples median difference

Source: R/statpsych1.R
ci.median.ps.Rd

Computes a distribution-free confidence interval for a difference of population medians in a paired-samples design. This function also computes the standard error of each median and the covariance between the two estimated medians. Tied scores within each measurement are assumed to be rare.

Usage

ci.median.ps(alpha, y1, y2)

Arguments

alpha

alpha level for 1-alpha confidence

y1

vector of scores for measurement 1

y2

vector of scores for measurement 2 (paired with y1)

Value

Returns a 1-row matrix. The columns are:

  • Median1 - estimated median for measurement 1

  • Median2 - estimated median for measurement 2

  • Median1-Median2 - estimated difference of medians

  • SE1 - standard error of median 1

  • SE2 - standard error of median 2

  • COV - covariance of the two estimated medians

  • LL - lower limit of the confidence interval

  • UL - upper limit of the confidence interval

References

Bonett DG, Price RM (2020). “Interval estimation for linear functions of medians in within-subjects and mixed designs.” British Journal of Mathematical and Statistical Psychology, 73(2), 333–346. ISSN 0007-1102, doi:10.1111/bmsp.12171 .

Examples

y1 <- c(21.1, 4.9, 9.2, 12.4, 35.8, 18.1, 10.7, 22.9, 24.0, 1.2, 6.1, 8.3, 13.1, 16.2)
y2 <- c(67.0, 28.1, 30.9, 28.6, 52.0, 40.8, 25.8, 37.4, 44.9, 10.3, 14.9, 20.2, 28.8, 40.6)
ci.median.ps(.05, y1, y2)
#>  Median1 Median2 Median1-Median2       SE        LL        UL      SE1      SE2
#>    12.75   29.85           -17.1 3.704248 -24.36019 -9.839807 3.379695 4.968956
#>      COV
#>  11.1957

# Should return:
#  Median1 Median2 Median1-Median2       SE        LL        UL
#    12.75   29.85           -17.1 3.704248 -24.36019 -9.839807
#       SE1      SE2     COV
#  3.379695 4.968956 11.1957