ci.2x2.mean.ws {statpsych} | R Documentation |
Computes confidence intervals and tests for the AB interaction effect, main effect of A, main efect of B, simple main effects of A, and simple main effects of B in a 2x2 within-subjects design with a quantitative response variable.
ci.2x2.mean.ws(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 - p-value
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
y11 = c(1,2,3,4,5,7,7) y12 = c(1,0,2,4,3,8,7) y21 = c(4,5,6,7,8,9,8) y22 = c(5,6,8,7,8,9,9) ci.2x2.mean.ws(.05, y11, y12, y21, y22) # Should return: # Estimate SE t df p LL UL # AB: 1.28571429 0.5654449 2.2738102 6 0.0633355395 -0.09787945 2.66930802 # A: -3.21428571 0.4862042 -6.6109784 6 0.0005765210 -4.40398462 -2.02458681 # B: -0.07142857 0.2296107 -0.3110855 6 0.7662600658 -0.63326579 0.49040865 # A at b1: -2.57142857 0.2973809 -8.6469203 6 0.0001318413 -3.29909331 -1.84376383 # A at b2: -3.85714286 0.7377111 -5.2285275 6 0.0019599725 -5.66225692 -2.05202879 # B at a1: 0.57142857 0.4285714 1.3333333 6 0.2308094088 -0.47724794 1.62010508 # B at a2: -0.71428571 0.2857143 -2.5000000 6 0.0465282323 -1.41340339 -0.01516804