ReactTime: Reaction Time Data

In heplots: Visualizing Hypothesis Tests in Multivariate Linear Models

Description

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.

Usage

data(ReactTime)

Format

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

Source

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

References

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.

Examples

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)
	}
	)

Example output

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

heplots documentation built on May 31, 2017, 4:54 a.m.