
Last chance! 50% off unlimited learning
Sale ends in
plotEst( ests, y = dim(ests)[1]:1, txt = rownames(ests), txtpos = y, ylim = range(y)-c(0.5,0), xlab = "", xtic = nice(ests[!is.na(ests)], log = xlog), xlim = range( xtic ), xlog = FALSE, pch = 16, cex = 1, lwd = 2, col = "black", col.txt = "black", font.txt = 1, col.lines = col, col.points = col, vref = NULL, grid = FALSE, col.grid = gray(0.9), restore.par = TRUE, ... )
linesEst( ests, y = dim(ests)[1]:1, pch = 16, cex = 1, lwd = 2, col="black", col.lines=col, col.points=col, ... )
pointsEst( ests, y = dim(ests)[1]:1, pch = 16, cex = 1, lwd = 2, col="black", col.lines=col, col.points=col, ... )
ci.lin
is
invoked for this object first.y
.grid
.FALSE
the coordinate system will still be available for
additional plotting, and par("mai")
will still have the very
large value set in order to make room for the labelling of the
estimates.ci.lin
when a model object is
supplied as ests
.plotEst
makes a news plot, whereas linesEst
and
pointsEst
(identical functions) adds to an existing plot. If a model object of class "glm"
, "coxph"
, "clogistic"
or
"gnlm"
is supplied the argument xlog
defaults to
TRUE
, and exponentiated estimates are extracted by default.
# 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 )
Run the code above in your browser using DataLab