R/statpsych1.R
ci.2x2.median.mixed.RdComputes distribution-free confidence intervals for the AB interaction effect, main effect of A, main effect of B, simple main effects of A, and simple main effects of B in a 2x2 mixed design where Factor A is the within-subjects factor and Factor B is the between-subjects factor. Effects are defined in terms of medians rather than means. Tied scores are assumed to be rare.
ci.2x2.median.mixed(alpha, y11, y12, y21, y22)alpha level for 1-alpha confidence
vector of scores at level 1 of A in group 1
vector of scores at level 2 of A in group 1
vector of scores at level 1 of A in group 2
vector of scores at level 2 of A in group 2
Returns a 7-row matrix (one row per effect). The columns are:
Estimate - estimate of effect
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
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 .
y11 <- c(18.3, 19.5, 20.1, 17.4, 20.5, 16.1)
y12 <- c(19.1, 18.4, 19.8, 20.0, 17.2, 16.8)
y21 <- c(19.2, 16.4, 16.5, 14.0, 16.9, 18.3)
y22 <- c(16.5, 10.2, 12.7, 9.9, 13.5, 15.0)
ci.2x2.median.mixed(.05, y11, y12, y21, y22)
#> Estimate SE LL UL
#> AB: -3.450 1.6317863 -6.6482423 -0.2517577
#> A: 1.875 0.8158931 0.2758788 3.4741212
#> B: 3.925 1.4262367 1.1296274 6.7203726
#> A at b1: 0.150 1.4243192 -2.6416144 2.9416144
#> A at b2: 3.600 0.7962670 2.0393454 5.1606546
#> B at a1: 2.200 1.5812792 -0.8992503 5.2992503
#> B at a2: 5.650 1.7027101 2.3127496 8.9872504
# Should return:
# Estimate SE LL UL
# AB: -3.450 1.6317863 -6.6482423 -0.2517577
# A: 1.875 0.8158931 0.2758788 3.4741212
# B: 3.925 1.4262367 1.1296274 6.7203726
# A at b1: 0.150 1.4243192 -2.6416144 2.9416144
# A at b2: 3.600 0.7962670 2.0393454 5.1606546
# B at a1: 2.200 1.5812792 -0.8992503 5.2992503
# B at a2: 5.650 1.7027101 2.3127496 8.9872504