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)

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

Examples

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