R/statpsych1.R
ci.2x2.median.bs.Rd
Computes confidence intervals for the AB interaction effect, main effect of A, main efect of B, simple main effects of A, and simple main effects of B in a 2x2 between-subjects design with a quantitative response variable. The effects are defined in terms of medians rather than means.
ci.2x2.median.bs(alpha, y11, y12, y21, y22)
alpha level for 1-alpha confidence
vector of scores at level 1 of A and level 1 of B
vector of scores at level 1 of A and level 2 of B
vector of scores at level 2 of A and level 1 of B
vector of scores at level 2 of A and level 2 of B
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
y11 = c(14, 15, 11, 7, 16, 12, 15, 16, 10, 9)
y12 = c(18, 24, 14, 18, 22, 21, 16, 17, 14, 13)
y21 = c(16, 11, 10, 17, 13, 18, 12, 16, 6, 15)
y22 = c(18, 17, 11, 9, 9, 13, 18, 15, 14, 11)
ci.2x2.median.bs(.05, y11, y12, y21, y22)
#> Estimate SE LL UL
#> AB: -5.0 3.389735 -11.643758 1.64375833
#> A: 1.5 1.694867 -1.821879 4.82187916
#> B: -2.0 1.694867 -5.321879 1.32187916
#> A at b1: -1.0 2.152661 -5.219138 3.21913797
#> A at b2: 4.0 2.618464 -1.132095 9.13209504
#> B at a1: -4.5 2.311542 -9.030539 0.03053939
#> B at a2: 0.5 2.479330 -4.359397 5.35939682
# Should return:
# Estimate SE LL UL
# AB: -5.0 3.389735 -11.643758 1.64375833
# A: 1.5 1.694867 -1.821879 4.82187916
# B: -2.0 1.694867 -5.321879 1.32187916
# A at b1: -1.0 2.152661 -5.219138 3.21913797
# A at b2: 4.0 2.618464 -1.132095 9.13209504
# B at a1: -4.5 2.311542 -9.030539 0.03053939
# B at a2: 0.5 2.479330 -4.359397 5.35939682