apc.frame | R Documentation |
A plot is generated where both the age-scale and the cohort/period scale is on the x-axis. The left vertical axis will be a logarithmic rate scale referring to age-effects and the right a logarithmic rate-ratio scale of the same relative extent as the left referring to the cohort and period effects (rate ratios).
Only an empty plot frame is generated. Curves or points must be added
with points
, lines
or the special utility function
apc.lines
.
apc.frame( a.lab,
cp.lab,
r.lab,
rr.lab = r.lab / rr.ref,
rr.ref = r.lab[length(r.lab)/2],
a.tic = a.lab,
cp.tic = cp.lab,
r.tic = r.lab,
rr.tic = r.tic / rr.ref,
tic.fac = 1.3,
a.txt = "Age",
cp.txt = "Calendar time",
r.txt = "Rate per 100,000 person-years",
rr.txt = "Rate ratio",
ref.line = TRUE,
gap = diff(range(c(a.lab, a.tic)))/10,
col.grid = gray(0.85),
sides = c(1,2,4) )
a.lab |
Numerical vector of labels for the age-axis. |
cp.lab |
Numerical vector of labels for the cohort-period axis. |
r.lab |
Numerical vector of labels for the rate-axis (left vertical) |
rr.lab |
Numerical vector of labels for the RR-axis (right vertical) |
rr.ref |
At what level of the rate scale is the RR=1 to be. |
a.tic |
Location of additional tick marks on the age-scale |
cp.tic |
Location of additional tick marks on the cohort-period-scale |
r.tic |
Location of additional tick marks on the rate-scale |
rr.tic |
Location of additional tick marks on the RR-axis. |
tic.fac |
Factor with which to diminish intermediate tick marks |
a.txt |
Text for the age-axis (left part of horizontal axis). |
cp.txt |
Text for the cohort/period axis (right part of horizontal axis). |
r.txt |
Text for the rate axis (left vertical axis). |
rr.txt |
Text for the rate-ratio axis (right vertical axis) |
ref.line |
Logical. Should a reference line at RR=1 be drawn at the calendar time part of the plot? |
gap |
Gap between the age-scale and the cohort-period scale |
col.grid |
Colour of the grid put in the plot. |
sides |
Numerical vector indicating on which sides axes should be drawn and annotated. This option is aimed for multi-panel displays where axes only are put on the outer plots. |
The function produces an empty plot frame for display of results
from an age-period-cohort model, with age-specific rates in the left
side of the frame and cohort and period rate-ratio parameters in the
right side of the frame. There is a gap of gap
between the
age-axis and the calendar time axis, vertical grid lines at
c(a.lab,a.tic,cp.lab,cp.tic)
, and horizontal grid lines at
c(r.lab,r.tic)
.
The function returns a numerical vector of
length 2, with names c("cp.offset","RR.fac")
. The y-axis for
the plot will be a rate scale for the age-effects, and the x-axis will
be the age-scale. The cohort and period effects are plotted by
subtracting the first element (named "cp.offset"
) of the returned result
form the cohort/period, and multiplying the rate-ratios by the second
element of the returned result (named "RR.fac"
).
A numerical vector of length two, with names
c("cp.offset","RR.fac")
. The first is the offset for the cohort
period-axis, the second the multiplication factor for the rate-ratio
scale.
Side-effect: A plot with axes and grid lines but no points or curves.
Moreover, the option apc.frame.par
is given the value
c("cp.offset","RR.fac")
, which is recognized by apc.plot
and apc.lines
.
Bendix Carstensen, Steno Diabetes Center, http://bendixcarstensen.com
B. Carstensen: Age-Period-Cohort models for the Lexis diagram. Statistics in Medicine, 26: 3018-3045, 2007.
apc.lines,apc.fit
par( mar=c(4,4,1,4) )
res <-
apc.frame( a.lab=seq(30,90,20), cp.lab=seq(1880,2000,30), r.lab=c(1,2,5,10,20,50),
a.tic=seq(30,90,10), cp.tic=seq(1880,2000,10), r.tic=c(1:10,1:5*10),
gap=27 )
res
# What are the axes actually?
par(c("usr","xlog","ylog"))
# How to plot in the age-part: a point at (50,10)
points( 50, 10, pch=16, cex=2, col="blue" )
# How to plot in the cohort-period-part: a point at (1960,0.3)
points( 1960-res[1], 0.3*res[2], pch=16, cex=2, col="red" )
# or referring to the period-cohort part of the plot
pc.points( 1960, 0.3, pch=16, cex=1, col="green" )
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