ci.2x2.stdmean.bs | R Documentation |
Computes confidence intervals for standardized 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. Equality of population variances is not assumed. A square root unweighted average variance standardizer is used, which is the recommended standardizer when both factors are treatment factors.
ci.2x2.stdmean.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 standardized effect
adj Estimate - bias adjusted estimate of standardized effect
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
Bonett2008statpsych
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.stdmean.bs(.05, y11, y12, y21, y22)
# Should return:
# Estimate adj Estimate SE LL UL
# AB: -1.44976487 -1.4193502 0.6885238 -2.7992468 -0.1002829
# A: 0.46904158 0.4592015 0.3379520 -0.1933321 1.1314153
# B: -0.75330920 -0.7375055 0.3451209 -1.4297338 -0.0768846
# A at b1: -0.25584086 -0.2504736 0.4640186 -1.1653006 0.6536189
# A at b2: 1.19392401 1.1688767 0.5001423 0.2136630 2.1741850
# B at a1: -1.47819163 -1.4471806 0.4928386 -2.4441376 -0.5122457
# B at a2: -0.02842676 -0.0278304 0.4820369 -0.9732017 0.9163482
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