ci.2x2.stdmean.bs {statpsych} | R Documentation |
Computes confidence intervals of standardized effects in a 2x2 between-subjects design for means
Description
Computes confidence intervals for standardized linear constrasts of means (AB interaction, 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. Equality of population variances is not assumed. An unweigthed variance standardizer is used, which is the recommended standarizer when both factors are treatment factors.
Usage
ci.2x2.stdmean.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 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
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.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