tinting {DAAG} | R Documentation |
These data are from an experiment that aimed to model the effects of the tinting of car windows on visual performance. The authors were mainly interested in effects on side window vision, and hence in visual recognition tasks that would be performed when looking through side windows.
tinting
This data frame contains the following columns:
f
female,
m
maleno
< lo
< hi
locon
: low contrast,
hicon
: high contrast younger
, 21-27,
older
, 70-78 Visual light transmittance (VLT) levels were 100% (tint=none), 81.3% (tint=lo), and 35.1% (tint=hi). Based on these and other data, Burns et al. argue that road safety may be compromised if the front side windows of cars are tinted to 35
Burns, N.R., Nettlebeck, T., White, M. and Willson, J., 1999. Effects of car window tinting on visual performance: a comparison of younger and older drivers. Ergonomics 42: 428-443.
require(lattice) levels(tinting$agegp) <- capstring(levels(tinting$agegp)) xyplot(csoa ~ it | sex * agegp, data=tinting) # Simple use of xyplot() pause() xyplot(csoa ~ it|sex*agegp, data=tinting, panel=panel.superpose, groups=target) pause() xyplot(csoa ~ it|sex*agegp, data=tinting, panel=panel.superpose, col=1:2, groups=target, key=list(x=0.14, y=0.84, points=list(pch=rep(1,2), col=1:2), text=list(levels(tinting$target), col=1:2), border=TRUE)) pause() xyplot(csoa ~ it|sex*agegp, data=tinting, panel=panel.superpose, groups=tint, type=c("p","smooth"), span=0.8, col=1:3, key=list(x=0.14, y=0.84, points=list(pch=rep(1,2), col=1:3), text=list(levels(tinting$tint), col=1:3), border=TRUE))