Computes tests and confidence intervals of effects in a 2x2 mixed 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 mixed factorial design with a quantitative response variable where Factor A is a within-subjects factor, and Factor B is a between-subjects factor. A Satterthwaite adjustment to the degrees of freedom is used and equality of population variances is not assumed.

ci.2x2.mean.mixed(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(18, 19, 20, 17, 20, 16)
y12 <- c(19, 18, 19, 20, 17, 16)
y21 <- c(19, 16, 16, 14, 16, 18)
y22 <- c(16, 10, 12,  9, 13, 15)
ci.2x2.mean.mixed(.05, y11, y12, y21, y22)
#>            Estimate        SE         t       df            p         LL
#> AB:      -3.8333333 0.9803627 -3.910117 8.346534 0.0041247610 -6.0778198
#> A:        2.0833333 0.4901814  4.250128 8.346534 0.0025414549  0.9610901
#> B:        3.7500000 1.0226599  3.666908 7.601289 0.0069250119  1.3700362
#> A at b1:  0.1666667 0.8333333  0.200000 5.000000 0.8493605140 -1.9754849
#> A at b2:  4.0000000 0.5163978  7.745967 5.000000 0.0005732451  2.6725572
#> B at a1:  1.8333333 0.9803627  1.870056 9.943850 0.0911668588 -0.3527241
#> B at a2:  5.6666667 1.2692955  4.464419 7.666363 0.0023323966  2.7173445
#>                 UL
#> AB:      -1.588847
#> A:        3.205577
#> B:        6.129964
#> A at b1:  2.308818
#> A at b2:  5.327443
#> B at a1:  4.019391
#> B at a2:  8.615989

# Should return:
#            Estimate        SE         t       df            p         LL        UL
# AB:      -3.8333333 0.9803627 -3.910117 8.346534 0.0041247610 -6.0778198 -1.588847
# A:        2.0833333 0.4901814  4.250128 8.346534 0.0025414549  0.9610901  3.205577
# B:        3.7500000 1.0226599  3.666908 7.601289 0.0069250119  1.3700362  6.129964
# A at b1:  0.1666667 0.8333333  0.200000 5.000000 0.8493605140 -1.9754849  2.308818
# A at b2:  4.0000000 0.5163978  7.745967 5.000000 0.0005732451  2.6725572  5.327443
# B at a1:  1.8333333 0.9803627  1.870056 9.943850 0.0911668588 -0.3527241  4.019391
# B at a2:  5.6666667 1.2692955  4.464419 7.666363 0.0023323966  2.7173445  8.615989