ci.2x2.mean.bs | R Documentation |
Computes confidence intervals and tests 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 design with a quantitative response variable. A Satterthwaite adjustment to the degrees of freedom is used and equality of population variances is not assumed.
ci.2x2.mean.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
t - t test statistic
df - degrees of freedom
p - two-sided p-value
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
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.mean.bs(.05, y11, y12, y21, y22)
# Should return:
# Estimate SE t df p LL UL
# AB: -5.10 2.224860 -2.29227953 35.47894 0.027931810 -9.6145264 -0.5854736
# A: 1.65 1.112430 1.48323970 35.47894 0.146840430 -0.6072632 3.9072632
# B: -2.65 1.112430 -2.38217285 35.47894 0.022698654 -4.9072632 -0.3927368
# A at b1: -0.90 1.545244 -0.58243244 17.56296 0.567678242 -4.1522367 2.3522367
# A at b2: 4.20 1.600694 2.62386142 17.93761 0.017246053 0.8362274 7.5637726
# B at a1: -5.20 1.536952 -3.38331916 17.61093 0.003393857 -8.4341379 -1.9658621
# B at a2: -0.10 1.608657 -0.06216365 17.91650 0.951120753 -3.4807927 3.2807927
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