| Date: | Fri, 6 Jan 2006 12:59:45 -0800 |
| Reply-To: | Kevin <kboswe1@LSU.EDU> |
| Sender: | "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU> |
| From: | Kevin <kboswe1@LSU.EDU> |
| Organization: | http://groups.google.com |
| Subject: | Interpreting Proc Logistic- Odds ratios to probability |
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| Content-Type: | text/plain; charset="iso-8859-1" |
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Hello all and Happy New Year,
I am running analyses on the presence of fish associated with an
artificial reef and have a few questions regarding the interpretation
of the output.
My response variable is binary (FishPres= 0 or 1) with 4 explanatory
variables :
Season= 1, 2 (First 6 months or last 6 months of year)
Depth_Bin = 1, 2, 3 (Depth intervals)
Area_Infl = 1,2 (Area of influence of reef)
Quad= 1, 2, 3, 4 (Quadrant of reef)
Proc Logistic data=two descending order=data;
Class season depth_bin area_infl quad /param=glm;
Model fishpres (event='1')= season vert area_infl quad /expb;
Contrast 'Depth-Up vs. Mid&Low' vert -2 1 1 / estimate=exp;
Contrast 'Reef Area- (1-3 vs 4)' quad -1 -1 -1 3 /estimate=exp;
Contrast 'Reef Clusters- (1&3 vs 2&4)' quad 1 -1 1 -1 /estimate=exp;
Output out=next1 predicted=yhat lower=lcl upper=ucl;
run;
Odds Ratio Estimates
Point 95% Wald
Effect Estimate Confidence Limits
Season 1 vs 2 2.440 2.365 2.517
Depth_bin 1 vs 3 0.429 0.414 0.445
Depth_bin 2 vs 3 0.515 0.498 0.532
Area_infl 1 vs 2 2.329 2.255 2.405
Quad 1 vs 4 1.093 1.045 1.144
Quad 2 vs 4 1.479 1.420 1.540
Quad 3 vs 4 1.213 1.162 1.267
Contrast Rows Estimation and Testing Results
Contrast Type Row Est. ChiSq
Depth- Mid vs Lower(2 vs3) EXP 1 0.5150 <.0001
Quad- Reef habitats(1-3 vs 4) EXP 1 0.5098 <.0001
Quad- Reef Cluster(1&3 vs 2&4) EXP 1 0.8970 <.0003
I am trying to describe the distribution of fish associated with the
reef and am interested in the probability of detection given season,
and position on reef (depth, quad, etc.). given that these variables
are all categorical the output provides estimates and odd ratio
estimates for each level compared to the last (reference) level.
1. Given the above model, how do I construct probability estimates of
detecting a fish given depth or area_infl? Furthermore, could I derive
an estimate of the increase or decrease in probability with changes in
depth or position on reef using the odds ratio estimates provided in
the above output.
2. Must I incorporate an interaction term if I want to discuss fish
presence across depth intervals or reef attributes by season? The
reason I ask is becasue it takes approx 30 min to run the models with
the interaction term. Additionally, if I do include an interaction
term, how do I construct a contrast statment for the interaction
effect?
3. Can contrast estimates be interpreted as odds ratios? Some of the
contrasts I have constructed previously have (as I understand it)
replicated tests of the main effects, thereby producing the save values
as the odds ratios.
Many thanks and kind regards,
Kevin Boswell
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