On Dec 23, 2006, at 12:07 AM, Bob Green wrote:
<snip>
> The data consists of a series of pre and post variables, in a
> dataframe
> called 'offend'. I am interested in graphically depicting the pre
&
> post
> values for a factor variable called 'decision' which has 4 values :
> nusm,
> fit, unsound & unfit. An example of a pre and post variable is:
> pre.damage
> and post.damage (data below). I wanted to exclude all values = 0, and
> collapse the remaining values into 3 categories .e.g 1, 2-5, 6 plus.
>
> For each 'decision' group the final graph would contain the
> alternating pre
> and post values for 'damage'. For example, for 'fit' the
first bar
> would
> have a pre value = 18 & a post value = 4, the second pre bar would
> = 17 and
> the post bar = 2, and the third pre bar would = 2 & the post = 1.
<snip>
> > table(decision,pre.damage)
> pre.damage
> decision 0 1 2 3 4 5 6 7 8 9 10 11 13
> 14 20
> fit 89 18 9 4 2 2 1 0 0 1 0 0
> 0 0 0
> nusm 158 44 15 5 5 6 6 3 1 1 2 0 0
> 0 0
> unfit 27 2 2 0 0 1 0 0 0 0 0 0
> 0 0 0
> unsound 333 68 36 8 5 4 1 0 0 0 0 1 1 1 1
>
> > table(decision,post.damage)
> post.damage
> decision 0 1 2 3 4 5 6 7 10 12 13
> fit 119 4 1 1 0 0 0 0 1 0 0
> nusm 212 16 11 2 0 2 1 1 0 1 0
> unfit 31 1 0 0 0 0 0 0 0 0 0
> unsound 441 8 5 3 1 0 0 0 0 0 1
Could you please post commands to define the df 'offend'?
_____________________________
Professor Michael Kubovy
University of Virginia
Department of Psychology
USPS: P.O.Box 400400 Charlottesville, VA 22904-4400
Parcels: Room 102 Gilmer Hall
McCormick Road Charlottesville, VA 22903
Office: B011 +1-434-982-4729
Lab: B019 +1-434-982-4751
Fax: +1-434-982-4766
WWW: http://www.people.virginia.edu/~mk9y/