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

Source: R/statpsych1.R

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)

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

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.mean.bs(.05, y11, y12, y21, y22)
#>          Estimate       SE           t       df           p         LL
#> AB:         -5.10 2.224860 -2.29227953 35.47894 0.027931810 -9.6145264
#> A:           1.65 1.112430  1.48323970 35.47894 0.146840430 -0.6072632
#> B:          -2.65 1.112430 -2.38217285 35.47894 0.022698654 -4.9072632
#> A at b1:    -0.90 1.545244 -0.58243244 17.56296 0.567678242 -4.1522367
#> A at b2:     4.20 1.600694  2.62386142 17.93761 0.017246053  0.8362274
#> B at a1:    -5.20 1.536952 -3.38331916 17.61093 0.003393857 -8.4341379
#> B at a2:    -0.10 1.608657 -0.06216365 17.91650 0.951120753 -3.4807927
#>                  UL
#> AB:      -0.5854736
#> A:        3.9072632
#> B:       -0.3927368
#> A at b1:  2.3522367
#> A at b2:  7.5637726
#> B at a1: -1.9658621
#> B at a2:  3.2807927

# 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