ci.2x2.median.bs {statpsych} | R Documentation |
Computes tests and confidence intervals of effects in a 2x2 between-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 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.
Usage
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
References
Bonett DG, Price RM (2002). “Statistical inference for a linear function of medians: Confidence intervals, hypothesis testing, and sample size requirements.” Psychological Methods, 7(3), 370–383. ISSN 1939-1463, doi:10.1037/1082-989X.7.3.370.
Examples
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