# Bogus data and a linear model
f <- factor( sample( letters[1:5], 100, replace=TRUE ) )
x <- rnorm( 100 )
y <- 5 + 2 * as.integer( f ) + 0.8 * x + rnorm(100) * 2
m1 <- lm( y ~ f )
# Produce some confidence intervals for contrast to first level
( cf <- ci.lin( m1, subset=-1 )[,-(2:4)] )
# Plots with increasing amounts of bells and whistles
par( mfcol=c(3,2), mar=c(3,3,2,1) )
plotEst( cf )
plotEst( cf, grid=TRUE, cex=2, lwd=3 )
plotEst( cf, grid=TRUE, cex=2, col.points="red", col.lines="green" )
plotEst( cf, grid=TRUE, cex=2, col.points="red", col.lines="green",
xlog=TRUE, xtic=c(1:8), xlim=c(0.8,6) )
rownames( cf )[1] <- "Contrast to fa:\n fb"
plotEst( cf, grid=TRUE, cex=2, col.points=rainbow(4),
col.lines=rainbow(4), vref=1 )
#
etxt <- expression("Plain text, qouted",
"combined with maths:"*sqrt(a)*phi[c],
f^d*" Hb"*A[1][c],
eff^e*" kg/"*m^2)
plotEst( cf, txt=etxt, grid=TRUE, cex=2, col.points=rainbow(4),
col.lines =rainbow(4), vref=1 )
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