plot.nordpred: plots the predicted rates from a nordpred object
In haraldwf/nordpred: Prediction of cancer incidence (as used in the Nordpred project)

Description Usage Arguments Details Value Note for S-plus Author(s) References See Also Examples

plot.nordpred uses nordpred object to plot observed and predicted rates

## S3 method for class 'nordpred'
plot(x, incidence = TRUE, standpop = NULL,
  agegroups = "all", startplot = 1, xlab = "", ylab = "", main = "",
  labels = NULL, ylim = NULL, lty = c(1, 3), col = c(1, 1),
  new = TRUE, ...)

`x`	An object of class `nordpred` (see `nordpred.object`
`incidence`	Indicates whether to plot incidence or number of cases
`standpop`	A vector of weights for age standardisation. Default is no standardisation (crude rates), but using a standardisation (for the suitable no of age groups) is recommended
`agegroups`	Which agegroups to include
`startplot`	Numeric
`xlab,ylab,main,ylim,lty,col`	Arguments passed to `plot` and `par`
`labels`	character
`new`	Should a new plot be created (`new = TRUE` by default) or should new graphs be added to an existing plot (`new = FALSE`)?
`...`	Arguments passed to `plot`

This function is a method for the generic function plot for class nordpred. It can be invoked by calling plot for an object of the appropriate class, or directly by calling plot.nordpred regardless of the class of the object. For more available options, see plot. For details of the choice of prediction base, significance test for using recent slope, and for the power5 model, see Moller B., Fekjaer H. et al. (2002), see references.

object of class nordpred (see nordpred.object).

Powerlink is made via a special modification in S-PLUS. This works fine for the point estimates, but the variance estimates found via the glm-objects are wrong. For variance estimates, we would rather recommend using R.

Harald Fekjaer and Bjorn Moller (Cancer Registry of Norway)

A website for nordpred is available at: http://www.kreftregisteret.no/software/nordpred/
Background for the methods can be found in: Moller B., Fekjaer H., Hakulinen T., Sigvaldason H, Storm H. H., Talback M. and Haldorsen T 'Prediction of cancer incidence in the Nordic countries: Empirical comparison of different approaches' Statistics in Medicine 2003; 22:2751-2766
An application of the function, using all the default settings, can be found in: Moller B, Fekjaer H, Hakulinen T, Tryggvadottir L, Storm HH, Talback M, Haldorsen T. Prediction of cancer incidence in the Nordic countries up to the year 2020. Eur J Cancer Prev Suppl 2002; 11: S1-S96

Other nordpred: is.nordpred.estimate, nordpred.estimate; is.nordpred, nordpred; nordpred.estimate.object; nordpred.getpred; nordpred.object; nordpred.prediction; print.nordpred.estimate; print.nordpred; summary.nordpred

# data (Colon cancer for Norwegian males)
indata

# Create dataset with observed and predicted population
inpop <- cbind(inpop1, inpop2)

# Fit model & predict new incidence:
res <- nordpred(indata, inpop, startestage = 5, startuseage = 6,
         cuttrend = c(0, .25, .5, .75, .75))
res2 <- nordpred(indata, inpop, startestage = 5, startuseage = 6,
     cuttrend = c(0, .25, .5, .75, .75), linkfunc = 'poisson')

# Get results with stanardiziotion:
wstand <- c(0.12, 0.1, 0.09, 0.09, 0.08, 0.08, 0.06, 0.06, 0.06, 0.06,0.05,
            0.04, 0.04, 0.03, 0.02, 0.01, 0.005, 0.005)
round(nordpred.getpred(res, incidence = TRUE, standpop = NULL), 2)
round(nordpred.getpred(res, incidence = TRUE, standpop = wstand), 2)

# Plot results:
plot(res, standpop = wstand)

# Plot results with power5 and poisson links:
plot(res2, standpop = wstand)
plot(res, new = FALSE, lty = c(1, 2), standpop = wstand)

# Different cut trend scenarios, using average drift (recent = FALSE):
est <- nordpred.estimate(cases = indata, pyr = inpop, noperiod = 4, startestage = 5)
plot(nordpred.prediction(est, startuseage = 6, cuttrend = c(0,0,0,0,0),
     recent = FALSE), standpop = wstand, new = TRUE)
plot(nordpred.prediction(est, startuseage = 6, cuttrend = c(1,1,1,1,1),
     recent = FALSE), standpop = wstand, new = FALSE, lty = c(1,2))
plot(nordpred.prediction(est,startuseage=6,cuttrend=c(0,.25,.5,.75,.75),
     recent = FALSE), standpop = wstand, new = FALSE, lty = c(1,4))