Functions to plot rates from a table classified by age and calendar time (period)
Description
Produces plots of rates versus age, connected within period or cohort
(Aplot
), rates versus period connected within agegroups
(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.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70  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 ), ... )

Arguments
rates 
A twodimensional table (or array) with rates to be plotted. It is assumed that the first dimension is age and the second is period. 
which 
A character vector with elements from

age 
Numerical vector giving the means of the
ageclasses. Defaults to the rownames of 
per 
Numerical vector giving the means of the periods. Defaults
to the columnnames of 
grid 
Logical indicating whether a background grid should be drawn. 
a.grid 
Logical indicating whether a background grid on the ageaxis should be drawn. If numerical it indicates the agecoordinates of the grid. 
p.grid 
do. for the period. 
c.grid 
do. for the cohort. 
ygrid 
do. for the ratedimension. 
col.grid 
The colour of the grid. 
a.lim 
Range for the ageaxis. 
p.lim 
Range for the periodaxis. 
c.lim 
Range for the cohortaxis. 
ylim 
Range for the yaxis (rates). 
at 
Position of labels on the yaxis (rates). 
labels 
Labels to put on the yaxis (rates). 
a.lab 
Text on the ageaxis. Defaults to "Age". 
p.lab 
Text on the periodaxis. Defaults to "Date of diagnosis". 
c.lab 
Text on the cohortaxis. Defaults to "Date of birth". 
ylab 
Text on the rateaxis. Defaults to the name of the ratetable. 
type 
How should the curves be plotted. Defaults to 
lwd 
Width of the lines. Defaults to 2. 
lty 
Which type of lines should be used. Defaults to 1, a solid line. 
log.ax 
Character with letters from 
las 
see 
ann 
Should the curves be annotated? 
a.ann 
Logical indicating whether agecurves should be annotated. 
p.ann 
do. for periodcurves. 
c.ann 
do. for cohortcurves. 
xannx 
The fraction that the xaxis is expanded when curves are annotated. 
cex.ann 
Expansion factor for characters annotating curves. 
a.thin 
Vector of integers indicating which of the ageclasses should be labelled. 
p.thin 
do. for the periods. 
c.thin 
do. for the cohorts. 
col 
Colours for the curves. 
a.col 
Colours for the agecurves. 
p.col 
do. for the periodcurves. 
c.col 
do. for the cohortcurves. 
p.lines 
Should rates from the same period be connected? 
c.lines 
Should rates from the same cohort be connected? 
... 
Additional arguments pssed on to 
Details
Zero values of the rates are ignored. They are neiter in the plot nor in the calculation of the axis ranges.
Value
NULL
. The function is used for its sideeffect, the plot.
Author(s)
Bendix Carstensen, Steno Diabetes Center, http://BendixCarstensen.com
See Also
apc.frame
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  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 )
