Produces plots of rates versus age, connected within period or cohort
(Aplot), rates versus period connected within age-groups
(Pplot) and rates and rates versus date of birth cohort
(Cplot). rateplot is a wrapper for these, allowing
to produce the four classical displays with a single call.
rateplot( rates,
which = c("ap","ac","pa","ca"),
age = as.numeric( dimnames( rates )[[1]] ),
per = as.numeric( dimnames( rates )[[2]] ),
grid = FALSE,
a.grid = grid,
p.grid = grid,
c.grid = grid,
ygrid = grid,
col.grid = gray( 0.9 ),
a.lim = range( age, na.rm=TRUE ) + c(0,diff( range( age ) )/30),
p.lim = range( per, na.rm=TRUE ) + c(0,diff( range( age ) )/30),
c.lim = NULL,
ylim = range( rates[rates>0], na.rm=TRUE ),
at = NULL,
labels = paste( at ),
a.lab = "Age at diagnosis",
p.lab = "Date of diagnosis",
c.lab = "Date of birth",
ylab = "Rates",
type = "l",
lwd = 2,
lty = 1,
log.ax = "y",
las = 1,
ann = FALSE,
a.ann = ann,
p.ann = ann,
c.ann = ann,
xannx = 1/20,
cex.ann = 0.8,
a.thin = seq( 1, length( age ), 2 ),
p.thin = seq( 1, length( per ), 2 ),
c.thin = seq( 2, length( age ) + length( per ) - 1, 2 ),
col = par( "fg" ),
a.col = col,
p.col = col,
c.col = col,
... )Aplot( rates, age = as.numeric( dimnames( rates )[[1]] ),
per = as.numeric( dimnames( rates )[[2]] ), grid = FALSE,
a.grid = grid, ygrid = grid, col.grid = gray( 0.9 ),
a.lim = range( age, na.rm=TRUE ), ylim = range( rates[rates>0], na.rm=TRUE ),
at = NULL, labels = paste( at ), a.lab = names( dimnames( rates ) )[1],
ylab = deparse( substitute( rates ) ), type = "l", lwd = 2, lty = 1,
col = par( "fg" ), log.ax = "y", las = 1, c.col = col, p.col = col,
c.ann = FALSE, p.ann = FALSE, xannx = 1/20, cex.ann = 0.8,
c.thin = seq( 2, length( age ) + length( per ) - 1, 2 ),
p.thin = seq( 1, length( per ), 2 ), p.lines = TRUE,
c.lines = !p.lines, ... )
Pplot( rates, age = as.numeric( dimnames( rates )[[1]] ),
per = as.numeric( dimnames( rates )[[2]] ), grid = FALSE,
p.grid = grid, ygrid = grid, col.grid = gray( 0.9 ),
p.lim = range( per, na.rm=TRUE ) + c(0,diff(range(per))/30),
ylim = range( rates[rates>0], na.rm=TRUE ), p.lab = names( dimnames( rates ) )[2],
ylab = deparse( substitute( rates ) ), at = NULL, labels = paste( at ),
type = "l", lwd = 2, lty = 1, col = par( "fg" ), log.ax = "y",
las = 1, ann = FALSE, cex.ann = 0.8, xannx = 1/20,
a.thin = seq( 1, length( age ), 2 ), ... )
Cplot( rates, age = as.numeric( rownames( rates ) ),
per = as.numeric( colnames( rates ) ), grid = FALSE,
c.grid = grid, ygrid = grid, col.grid = gray( 0.9 ),
c.lim = NULL, ylim = range( rates[rates>0], na.rm=TRUE ),
at = NULL, labels = paste( at ), c.lab = names( dimnames( rates ) )[2],
ylab = deparse( substitute( rates ) ), type = "l", lwd = 2, lty = 1,
col = par( "fg" ), log.ax = "y", las = 1, xannx = 1/20, ann = FALSE,
cex.ann = 0.8, a.thin = seq( 1, length( age ), 2 ), ... )
NULL. The function is used for its side-effect, the plot.
A two-dimensional table (or array) with rates to be plotted. It is assumed that the first dimension is age and the second is period.
A character vector with elements from
c("ap","ac","apc","pa","ca"), indication which plots should
be produced. One plot per element is produced. The first letter
indicates the x-axis of the plot, the remaining which groups
should be connected, i.e. "pa" will plot rates versus
period and connect age-classes, and "apc" will plot rates
versus age, and connect both periods and cohorts.
Numerical vector giving the means of the
age-classes. Defaults to the rownames of rates as numeric.
Numerical vector giving the means of the periods. Defaults
to the columnnames of rates as numeric.
Logical indicating whether a background grid should be drawn.
Logical indicating whether a background grid on the age-axis should be drawn. If numerical it indicates the age-coordinates of the grid.
do. for the period.
do. for the cohort.
do. for the rate-dimension.
The colour of the grid.
Range for the age-axis.
Range for the period-axis.
Range for the cohort-axis.
Range for the y-axis (rates).
Position of labels on the y-axis (rates).
Labels to put on the y-axis (rates).
Text on the age-axis. Defaults to "Age".
Text on the period-axis. Defaults to "Date of diagnosis".
Text on the cohort-axis. Defaults to "Date of birth".
Text on the rate-axis. Defaults to the name of the rate-table.
How should the curves be plotted. Defaults to "l".
Width of the lines. Defaults to 2.
Which type of lines should be used. Defaults to 1, a solid line.
Character with letters from "apcyr", indicating
which axes should be logarithmic. "y" and "r" both
refer to the rate scale. Defaults to "y".
see par.
Should the curves be annotated?
Logical indicating whether age-curves should be annotated.
do. for period-curves.
do. for cohort-curves.
The fraction that the x-axis is expanded when curves are annotated.
Expansion factor for characters annotating curves.
Vector of integers indicating which of the age-classes should be labelled.
do. for the periods.
do. for the cohorts.
Colours for the curves.
Colours for the age-curves.
do. for the period-curves.
do. for the cohort-curves.
Should rates from the same period be connected?
Should rates from the same cohort be connected?
Additional arguments pssed on to matlines when
plotting the curves.
Bendix Carstensen, Steno Diabetes Center, http://bendixcarstensen.com
Zero values of the rates are ignored. They are neiter in the plot nor in the calculation of the axis ranges.
apc.frame
data( blcaIT )
attach(blcaIT)
# Table of rates:
bl.rate <- tapply( D, list(age,period), sum ) /
tapply( Y, list(age,period), sum )
bl.rate
# The four classical plots:
par( mfrow=c(2,2) )
rateplot( bl.rate*10^6 )
# The labels on the vertical axis could be nicer:
rateplot( bl.rate*10^6, at=10^(-1:3), labels=c(0.1,1,10,100,1000) )
# More bells an whistles
par( mfrow=c(1,3), mar=c(3,3,1,1), oma=c(0,3,0,0), mgp=c(3,1,0)/1.6 )
rateplot( bl.rate*10^6, ylab="", ann=TRUE, which=c("AC","PA","CA"),
at=10^(-1:3), labels=c(0.1,1,10,100,1000),
col=topo.colors(11), cex.ann=1.2 )
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