LISTSERV at the University of Georgia
Menubar Imagemap
Home Browse Manage Request Manuals Register
Previous messageNext messagePrevious in topicNext in topicPrevious by same authorNext by same authorPrevious page (January 2006, week 1)Back to main SAS-L pageJoin or leave SAS-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:         Thu, 5 Jan 2006 13:07:47 -0800
Reply-To:     Steve <sczapka@HOTMAIL.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Steve <sczapka@HOTMAIL.COM>
Organization: http://groups.google.com
Subject:      Re: Estimate Statements with continuous variables
Comments: To: sas-l@uga.edu
In-Reply-To:  <20051227184458.83762.qmail@web32202.mail.mud.yahoo.com>
Content-Type: text/plain; charset="iso-8859-1"

I probably should have added to my original listing that I would be running the analysis on a sub-set of the data only containing data from seedlings that were protected by shelters. I realize that the analysis would be confounded by control seedlings (shelter diameter of zero).

-Steve

Dale McLerran wrote: > --- Steve <sczapka@HOTMAIL.COM> wrote: > > > Greetings. > > > > I am analyzing tree seedling growth in response to various treatments > > using PROC MIXED. Treatments include the use of tree shelters to > > protect the seedlings, herbicide to control competing vegetation, and > > different species. I now want to include tree shelter diameter (a > > continuous variable) as a covariate. However, I'm not exactly sure > > how > > to further analyze a significant interaction between for example tree > > shelter use and shelter diameter. > > > > As an example, say my model is the following.... > > > > PROC MIXED; > > CLASS shelter herbicide species; > > MODEL growth = shelter herbicide species diameter > > shelter*herbicide shelter*species > > shelter*diameter; > > > > In the event of a significant shelter*diameter interaction, how can I > > determine where the differences exist? In ther past I've only > > compared > > two categorical variables (e.g., shelter*herbicide). In that > > instance > > I used estimated statements to determine where the differences lied. > > > > For example, say I had a significant shelter*herbicide interaction. > > If > > I wanted to compare sheltered versus unsheltered seedlings when > > Herbicide was used or not, I could write two estimated statements > > like... > > ESTIMATE "shelter v. unsheltered, herbicide" shelter 1 -1 > > shelter*herbicide 1 0 -1 0; > > ESTIMATE "shelter v. unsheltered, no herbicide" shelter 1 -1 > > shelter*herbcide 0 1 0 -1; > > > > In this instance SAS gives me a p-value I can use to determine > > significant differences between the different levels. > > > > Someone told me I can do the same sort of thing with a continous > > variable by "comparing effect (beta) estimates for the different > > levels > > of the categorical variable", but I'm not sure how to do this in SAS. > > Can anyone offer advice as to how this may be accomplished? > > > > Thank you. > > Steve Czapka > > > > Steve, > > I believe there is a conceptual problem here. You indicate > that the shelter variable is an indicator of whether the > seedlings are sheltered or unsheltered. If the seedlings > are unsheltered, then you must set the shelter diameter to > zero, right? Note that the shelter diameter cannot vary for > unsheltered seedlings. If the seedlings are sheltered, then > the shelter diameter is nonzero and can vary. > > Thus, the shelter diameters for sheltered and unsheltered > seedlings are mutually exclusive of each other. Further, > there is NO SLOPE FOR THE SHELTER DIAMETER EFFECT when the > seedlings are unsheltered. Since there can be no slope for > the shelter diameter effect, then how can you estimate and > interpret an interaction effect? > > The estimate could only be obtained by extrapolating the > shelter diameter effect for sheltered trees to zero diameter. > Depicted graphically, you might have an effect something > like the following: > > Growth > | G > | > | G > | > | G > | > | G > | > |g > | > | > | > |G > | > ------------------------------------------------- > 0 1 2 3 4 > > Shelter diameter > > > Here, the upper case G represents mean value given the > fitted model. Note that the upper case G at shelter > diameter zero is for an unsheltered tree. The other three > upper case G values are mean growth for sheltered trees > with diameters 1, 2, 3, and 4. The lower case g is an > extrapolation of the effect of shelter diameter in sheltered > trees to a shelter diameter of zero. The difference between > extrapolated zero shelter diameter for a sheltered tree and > the observed zero shelter diameter for an unsheltered tree > is the only basis for an interaction effect. This difference > may be "significant", but it seems to me completely > uninterpretable. > > Dale > > > --------------------------------------- > Dale McLerran > Fred Hutchinson Cancer Research Center > mailto: dmclerra@NO_SPAMfhcrc.org > Ph: (206) 667-2926 > Fax: (206) 667-5977 > --------------------------------------- > > > > > __________________________________ > Yahoo! for Good - Make a difference this year. > http://brand.yahoo.com/cybergivingweek2005/


Back to: Top of message | Previous page | Main SAS-L page