| ci.2x2.median.bs | R Documentation |
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 between-subjects factorial design with a quantitative response variable. The effects are defined in terms of medians rather than means. Tied scores within each group are assumed to be rare.
For more details, see Section 3.21 of Bonett (2021, Volume 1)
ci.2x2.median.bs(alpha, y11, y12, y21, y22)
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 |
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
Bonett2002statpsych
\insertRefBonett2021statpsych
y11 <- c(19.2, 21.1, 14.4, 13.3, 19.8, 15.9, 18.0, 19.1, 16.2, 14.6)
y12 <- c(21.3, 27.0, 19.1, 21.5, 25.2, 24.1, 19.8, 19.7, 17.5, 16.0)
y21 <- c(16.5, 11.3, 10.3, 17.7, 13.8, 18.2, 12.8, 16.2, 6.1, 15.2)
y22 <- c(18.7, 17.3, 11.4, 12.4, 13.6, 13.8, 18.3, 15.0, 14.4, 11.9)
ci.2x2.median.bs(.05, y11, y12, y21, y22)
# Should return:
# Estimate SE LL UL
# AB: -3.850 2.951019 -9.633891 1.9338914
# A: 4.525 1.475510 1.633054 7.4169457
# B: -1.525 1.475510 -4.416946 1.3669457
# A at b1: 2.600 1.992028 -1.304302 6.5043022
# A at b2: 6.450 2.177232 2.182703 10.7172971
# B at a1: -3.450 2.045086 -7.458294 0.5582944
# B at a2: 0.400 2.127472 -3.769769 4.5697694
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