apc.plot.data.level: Level plot of data matrix.

In apc: Age-Period-Cohort Analysis

Description

This plot shows level plot of data matrix based on levelplot in the package lattice.

Usage

apc.plot.data.level(apc.data.list,data.type="r",
 						rotate=FALSE,apc.index=NULL,
						main=NULL,lab=NULL,
						contour=FALSE,colorkey=TRUE)

Arguments

apc.data.list	List. See apc.data.list for a description of the format.
data.type	Optional. Character. "r"="response" / "d"="dose" / "m"="mortality"="rates" if sums are computed for responses/dose/rates, where rates are found through division response/dose. It also takes data types "residual" / "fitted.values" / "linear.predictors" when the argument apc.data.list is the output of the fitting function apc.fit.model, which is an extended apc.data.list. "r" is default.
rotate	Optional. Logical. If TRUE rotates plot 90 degrees clockwise (or anti-clockwise if data.format is "CL"). Default is FALSE.
apc.index	Optional. List. See apc.get.index for a description of the format. If not provided this is computed.
main	Optional. Character. Main title.
lab	Optional plot parameter. A numerical vector of the form c(x, y, len) which modifies the default way that axes are annotated. The values of x and y give the (approximate) number of tickmarks on the x and y axes. len is not implemented.
contour	Optional levelplot (lattice) parameter. Logical. Contour lines drawn if TRUE. Default FALSE.
colorkey	Optional levelplot (lattice) parameter. Logical or list. Determines color key. Default TRUE.

Author(s)

Bent Nielsen <[e-mail]> 26 Apr 2015

See Also

data.Japanese.breast.cancer for information on the data used in the example.

Examples

#####################
#	EXAMPLE with Japanese breast cancer data
#	Clayton and Shifflers (1987b) use APC design
#	Make a data list
#	Then plot data.
#	Note: No plot appears to have approximately parallel lines.

data.list	<- data.Japanese.breast.cancer()
apc.plot.data.level(data.list,"r")
dev.new()
apc.plot.data.level(data.list,"d",contour=TRUE)
												
#	It also works with a single argument, but then a default log scale is used.
# 	Note that warnings are given in relation to the data chosen thinning

apc.plot.data.within(data.list)

#####################
#	EXAMPLE with Italian bladder cancer data
#	Clayton and Shifflers (1987a) use AC design
#	Note: plot of within cohort against age appears to have approximately parallel lines.
#		  This is Figure 2 in Clayton and Shifflers (1987a)
#	Note: plot of within age against cohort appears to have approximately parallel lines.
#		  Indicates that interpretation should be done carefully.

data.list	<- data.Italian.bladder.cancer()	
apc.plot.data.within(data.list,"m",1,log="y")

#####################
#	EXAMPLE with asbestos data
#	Miranda Martinex, Nielsen and Nielsen (2014).
#	This is Figure 1d 

data.list	<- data.asbestos()	
apc.plot.data.within(data.list,type="l",lty=1)

apc documentation built on Oct. 23, 2020, 6:17 p.m.