ci.2x2.stdmean.ws: Computes confidence intervals of standardized effects in a...
In statpsych: Statistical Methods for Psychologists
ci.2x2.stdmean.ws R Documentation
Computes confidence intervals of standardized effects in a 2x2
within-subjects design
Description
Computes confidence intervals for standardized linear constrasts of means
(AB interaction, 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.
Equality of population variances is not assumed. An unweigthed variance
standardizer is used.
Usage
ci.2x2.stdmean.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 - estimated standardized effect
adj Estimate - bias adjusted standardized effect estimate
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
Examples
y11 <- c(21, 39, 32, 29, 27, 17, 27, 21, 28, 17, 12, 27)
y12 <- c(20, 36, 33, 27, 28, 14, 30, 20, 27, 15, 11, 22)
y21 <- c(21, 36, 30, 27, 28, 15, 27, 18, 29, 16, 11, 22)
y22 <- c(18, 34, 29, 28, 28, 17, 27, 21, 26, 16, 14, 23)
ci.2x2.stdmean.ws(.05, y11, y12, y21, y22)
# Should return:
# Estimate adj Estimate SE LL UL
# AB: 0.17248839 0.16446123 0.13654635 -0.095137544 0.4401143
# A: 0.10924265 0.10415878 0.05752822 -0.003510596 0.2219959
# B: 0.07474497 0.07126653 0.05920554 -0.041295751 0.1907857
# A at b1: 0.19548684 0.18638939 0.08460680 0.029660560 0.3613131
# A at b2: 0.02299845 0.02192816 0.09371838 -0.160686202 0.2066831
# B at a1: 0.16098916 0.15349715 0.09457347 -0.024371434 0.3463498
# B at a2: -0.01149923 -0.01096408 0.08595873 -0.179975237 0.1569768
statpsych documentation built on June 22, 2024, 6:51 p.m.
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| ci.2x2.stdmean.ws | R Documentation |
Computes confidence intervals of standardized effects in a 2x2 within-subjects design
Description
Computes confidence intervals for standardized linear constrasts of means (AB interaction, 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. Equality of population variances is not assumed. An unweigthed variance standardizer is used.
Usage
ci.2x2.stdmean.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 - estimated standardized effect
adj Estimate - bias adjusted standardized effect estimate
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
Examples
y11 <- c(21, 39, 32, 29, 27, 17, 27, 21, 28, 17, 12, 27)
y12 <- c(20, 36, 33, 27, 28, 14, 30, 20, 27, 15, 11, 22)
y21 <- c(21, 36, 30, 27, 28, 15, 27, 18, 29, 16, 11, 22)
y22 <- c(18, 34, 29, 28, 28, 17, 27, 21, 26, 16, 14, 23)
ci.2x2.stdmean.ws(.05, y11, y12, y21, y22)
# Should return:
# Estimate adj Estimate SE LL UL
# AB: 0.17248839 0.16446123 0.13654635 -0.095137544 0.4401143
# A: 0.10924265 0.10415878 0.05752822 -0.003510596 0.2219959
# B: 0.07474497 0.07126653 0.05920554 -0.041295751 0.1907857
# A at b1: 0.19548684 0.18638939 0.08460680 0.029660560 0.3613131
# A at b2: 0.02299845 0.02192816 0.09371838 -0.160686202 0.2066831
# B at a1: 0.16098916 0.15349715 0.09457347 -0.024371434 0.3463498
# B at a2: -0.01149923 -0.01096408 0.08595873 -0.179975237 0.1569768
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