apc.plot.data.all {apc}

Make all descriptive plots.

Description

Plots data sums using apc.plot.data.sums. Sparsity plots of data using apc.plot.data.sparsity. Plots data using all combinations of two time scales using apc.plot.data.within. Level plots of data using apc.plot.data.level. The latter plot is done for responses and if applicable also for doses and mortality rates.

Usage

apc.plot.data.all(apc.data.list,log ="",rotate=FALSE)

Arguments

apc.data.list

List. See apc.data.list for a description of the format.

log

Optional plot argument. Character. "y" if y-scale is logarithmic, otherwise "". Default is "y".

rotate

Optional. Logical. If TRUE rotates apc.plot.data.level 90 degrees clockwise (or anti-clockwise if data.format is "CL"). Default is FALSE.

Warning

A warning is produced if dimension is not divisible by thin, so that one group is smaller than other groups.

Author(s)

Bent Nielsen <[e-mail]> 25 Apr 2015

See Also

The example below uses Italian bladder cancer data, see data.Italian.bladder.cancer

Examples

#####################
#  EXAMPLE with artificial data
#  generate a 3x4 matrix in "AP" data.format with the numbers 1..12

m.data  	<- matrix(data=seq(length.out=12),nrow=3,ncol=4)
m.data
data.list	<- apc.data.list(m.data,"AP")
apc.plot.data.all(data.list,log="")				

#####################
#	EXAMPLE with Italian bladder cancer data
#
#	get data list, then make all descriptive plots.
# 	Note that warnings are given in relation to the data chosen thinning
#	This can be avoided by working with the individual plots, and in particular
#	with apc.plot.data.within where the thinning happens.
#
#	data.list	<- data.Italian.bladder.cancer()	
#	apc.plot.data.all(data.list)