ci.2x2.median.ws {statpsych} | R Documentation |
Computes confidence intervals of effects in a 2x2 within-subjects design for medians
Description
Computes 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 within-subjects design. The effects are defined in terms of medians rather than means. Tied scores within each level combination are assumed to be rare.
Usage
ci.2x2.median.ws(alpha, y11, y12, y21, y22)
Arguments
alpha |
alpha level for 1-alpha confidence |
y11 |
vector of scores at level 1 of A and level 1 of B |
y12 |
vector of scores at level 1 of A and level 2 of B |
y21 |
vector of scores at level 2 of A and level 1 of B |
y22 |
vector of scores at level 2 of A and level 2 of B |
Value
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
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
y11 <- c(222, 402, 333, 301, 284, 182, 281, 230, 290, 182, 133, 278)
y12 <- c(221, 371, 340, 288, 293, 150, 317, 211, 286, 161, 126, 234)
y21 <- c(219, 371, 314, 279, 284, 155, 278, 185, 296, 169, 118, 229)
y22 <- c(170, 332, 280, 273, 272, 160, 260, 204, 252, 153, 137, 223)
ci.2x2.median.ws(.05, y11, y12, y21, y22)
# Should return:
# Estimate SE LL UL
# AB: 3.50 21.050122 -37.75748155 44.75748
# A: 24.25 9.603490 5.42750463 43.07250
# B: 17.75 9.101881 -0.08935904 35.58936
# A at b1: 26.00 11.813742 2.84549058 49.15451
# A at b2: 22.50 16.323093 -9.49267494 54.49267
# B at a1: 19.50 15.710347 -11.29171468 50.29171
# B at a2: 16.00 11.850202 -7.22596953 39.22597