ci.2x2.median.ws: Computes confidence intervals of effects in a 2x2...

In statpsych: Statistical Methods for Psychologists

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 factorial 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

\insertRef

Bonett2020statpsych

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

statpsych documentation built on June 10, 2025, 5:11 p.m.