Date: Thu, 19 Oct 2006 08:47:24 -0400
Reply-To: "data _null_;" <datanull@GMAIL.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: "data _null_;" <datanull@GMAIL.COM>
Subject: Re: Categorical variable codings
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
You fail to mention important items replication and design. How many
samples of each of the 90 treatment combinations do you have. Or do
you expect to estimate error from the 40 degree of freedom 3 way
interaction? Did you use blocking? Did you collect the samples using a
randomized design? If so what is it?
You can design an and randomize an experiment like this using SAS.
The following example may be helpful. This is greatly simplified and
probably does not apply directly to your data.
/*6 X 5 X 3 one replication */
proc plan seed=112358;
block = 1 ordered
oil = 6
material = 5
heatingTime = 3
output out=work.plan heatingTime nvals=(30 to 90 by 30);
unitID = put(_n_,z5.);
y = ranuni(122358);
class block oil material heatingTime;
model y = block oil|material|HeatingTime@2;
On 10/19/06, Chrissy Wissy <email@example.com> wrote:
> I am trying various regression analyses on data obtained from the study
> of 6 different cooking oils, control and 4 different material
> treatments, all samples being sampled at 30 min, 60 min and 90 min
> heating. I am wondering what a suitable set of categorical variable
> codes to use for comparing, e.g. material/time or oil/material/time,
> i.e. 5 X 3 or 6 X 5 X 3 at all levels and interactions, assuming with
> the latter that "oil" can be included as an independent variable.