Description Usage Format Source References Examples
Data from Maxwell and Delaney (1990, p. 497) representing the reaction times of 10 subjects in some task where visual stimuli are tilted at 0, 4, and 8 degrees; with noise absent or present. Each subject responded to 3 tilt x 2 noise = 6 conditions. The data thus comprise a repeated measure design with two within-S factors.
1 |
A data frame with 10 observations giving the reaction time for the 6 conditions.
deg0NA
a numeric vector
deg4NA
a numeric vector
deg8NA
a numeric vector
deg0NP
a numeric vector
deg4NP
a numeric vector
deg8NP
a numeric vector
Baron, J. and Li, Y. (2003). Notes on the use of R for psychology experiments and questionnaires, https://cran.r-project.org/doc/contrib/Baron-rpsych.pdf
Michael Friendly (2010). HE Plots for Repeated Measures Designs. Journal of Statistical Software, 37(4), 1-40. URL http://www.jstatsoft.org/v37/i04/.
Maxwell, S. E. & Delaney, H. D. (1990). Designing Experiments and Analyzing Data: A model comparison perspective. Pacific Grove, CA: Brooks/Cole.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | data(ReactTime)
(RT.mod <- lm(as.matrix(ReactTime)~1))
# within-S factors
within <- expand.grid(tilt=ordered(c(0,4,8)), noise=c("NA", "NP"))
Anova(RT.mod, idata=within, idesign=~tilt * noise)
heplot(RT.mod, idata=within, idesign=~tilt * noise, iterm="tilt")
# plotting means and std errors directly
levels <- expand.grid(Tilt=c(0,4,8), noise=c("NA", "NP"))
(means.df <- data.frame(levels, mean=colMeans(ReactTime), se=sqrt(diag(var(ReactTime)))/9))
with(means.df, {
plot(Tilt, mean, type="n", main="Reaction Time data", xlab="Tilt", ylab="Reaction time")
colors <- rep(c("red", "blue"), each=3)
pts <- rep(c(15, 16), each=3)
lines(Tilt[1:3], mean[1:3], col="red", lwd=2)
lines(Tilt[4:6], mean[4:6], col="blue", lwd=2)
points(Tilt, mean, pch=pts, col=colors, cex=1.2)
arrows(Tilt, mean-se, Tilt, mean+se, angle=90, code=3,
col=colors, len=.05, lwd=2)
# labels at last point, in lieu of legend
text(Tilt[3], mean[3]-10, labels="NA", col="red", pos=1)
text(Tilt[6], mean[6]-10, labels="NP", col="blue", pos=1)
}
)
|
Loading required package: car
Loading required package: carData
Call:
lm(formula = as.matrix(ReactTime) ~ 1)
Coefficients:
deg0NA deg4NA deg8NA deg0NP deg4NP deg8NP
(Intercept) 462 510 528 492 660 762
Note: model has only an intercept; equivalent type-III tests substituted.
Type III Repeated Measures MANOVA Tests: Pillai test statistic
Df test stat approx F num Df den Df Pr(>F)
(Intercept) 1 0.98518 598.45 1 9 1.527e-09 ***
tilt 1 0.88760 31.59 2 8 0.0001596 ***
noise 1 0.78955 33.77 1 9 0.0002560 ***
tilt:noise 1 0.91822 44.91 2 8 4.472e-05 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Note: model has only an intercept; equivalent type-III tests substituted.
Tilt noise mean se
deg0NA 0 NA 462 6.324555
deg4NA 4 NA 510 9.558139
deg8NA 8 NA 528 8.777075
deg0NP 0 NP 492 9.838197
deg4NP 4 NP 660 12.171612
deg8NP 8 NP 762 12.976712
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