ci.2x2.mean.ws: Computes tests and confidence intervals of effects in a 2x2...

In statpsych: Statistical Methods for Psychologists

Computes tests and confidence intervals of effects in a 2x2 within-subjects design for means

Description

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 within-subjects factorial design with a quantitative response variable.

For more details, see Section 4.14 of Bonett (2021, Volume 1)

Usage

ci.2x2.mean.ws(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

• 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

References

\insertRef

Bonett2021statpsych

Examples

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  2.2738  6 0.06334 -0.09787945  2.66930802
# A:       -3.21428571 0.4862042 -6.6110  6 0.00058 -4.40398462 -2.02458681
# B:       -0.07142857 0.2296107 -0.3111  6 0.76626 -0.63326579  0.49040865
# A at b1: -2.57142857 0.2973809 -8.6469  6 0.00013 -3.29909331 -1.84376383
# A at b2: -3.85714286 0.7377111 -5.2285  6 0.00196 -5.66225692 -2.05202879
# B at a1:  0.57142857 0.4285714  1.3333  6 0.23081 -0.47724794  1.62010508
# B at a2: -0.71428571 0.2857143 -2.5000  6 0.04653 -1.41340339 -0.01516804

statpsych documentation built on Jan. 13, 2026, 1:07 a.m.