ci.2x2.mean.mixed: Computes tests and confidence intervals of effects in a 2x2...
In statpsych: Statistical Methods for Psychologists
ci.2x2.mean.mixed R Documentation
Computes tests and confidence intervals of effects in a 2x2 mixed 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 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.
Usage
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)
# 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
statpsych documentation built on Sept. 11, 2024, 7:42 p.m.
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| ci.2x2.mean.mixed | R Documentation |
Computes tests and confidence intervals of effects in a 2x2 mixed 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 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.
Usage
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)
# 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
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