Hi
I need SAS commands to compare regression slopes, for the following data set,
most apprericated any help...
Options S = 40 LS = 78 NODATE center;
Data Comp;
Input Year $ Y X @@;
Cards;
1YR 3.8 4.5 2YR 6.8 4.5
1YR 6.2 7.5 2YR 15.2 16.5
1YR 7.2 9.5 2YR 8.5 8.0
1YR 8.7 10.5 2YR 9.1 9.5
1YR 10.2 13.0 2YR 12.0 11.5
1YR 13.5 16.0 2YR 12.6 13.0
2YR 13.3 14.0
;
Regards
Javad
I assume you want a model like this:
proc glm data=Comp;
class Year;
model Y = X | Year / solution;
run;
and then look at the parameter estimates. The estimate for X gives the baseline estimate (for Year=2Yr) and the estimate of the interaction term (X*(Year=1Yr) gives the incremental increase in for the Year=1Yr group.
Mr Rick
Thanks a lot, for the commands,
I guess I am almost close to the comparsion but not yet though.
I got estimates for different years, but NOT being compared
There letter B in separate columb, it seem there are non-formality implied there?
Source DF Type I SS Mean Square F Value Pr > F X Year X*Year
1 | 118.6625502 | 118.6625502 | 493.32 | <.0001 |
1 | 14.8438739 | 14.8438739 | 61.71 | <.0001 |
1 | 0.3717842 | 0.3717842 | 1.55 | 0.2452 |
Source DF Type III SS Mean Square F Value Pr > F X Year X*Year
1 | 108.3875717 | 108.3875717 | 450.60 | <.0001 |
1 | 3.4568736 | 3.4568736 | 14.37 | 0.0043 |
1 | 0.3717842 | 0.3717842 | 1.55 | 0.2452 |
Parameter Estimate Standard
Error t Value Pr > |t| Intercept X Year 1YR Year 2YR X*Year 1YR X*Year 2YR
2.980191458 | B | 0.57828994 | 5.15 | 0.0006 |
0.735567010 | B | 0.04979763 | 14.77 | <.0001 |
-3.122248485 | B | 0.82360741 | -3.79 | 0.0043 |
0.000000000 | B | . | . | . |
0.091520566 | B | 0.07361525 | 1.24 | 0.2452 |
0.000000000 | B | . | . | . |
looking at a similar question, I found the following commands but not working as it is: what do you think ?
ROC REG;
Model Y = X test b=the slope of model A ;
run;
Sorry, I thought you wanted the values of the slopes. If you want to test whether the slopes are statistically different, you can do a hypothesis test, as described in this SAS Note. For your data it would look like
ESTIMATE '1Yr VS 2Yr' Year 1 -1;
Yes, the "B" indicate the reference levels for the GLM parameterization. You can read about how to interpret the /SOLUTION output in the same SAS note.
Thanks once again,
you are very helpful
great reminder of what I was doing years ago, with contrast and estimate
Best Regards
Javad
Hi Rick
I was wondering if I can use estimate or contrast slopes of two years ( B1 vs B2) from regression lines, which are not titled in the data
any comment on these commands :
PROC REG;
Model Y = X test b=the slope of model A ;
run;
Yi = B0 + B1x + µ
Yii = B0 + B2x + µ
'B1 vs B2' ??
Thanks
Javad
I don't understand why you are now using PROC REG. Perhaps this is a different question. My guess is that you are asking for a hypothesis test to see if it is likely that a parameter estimate equals some value of the parameter. The TEST statement in PROC REG runs an F test for that hypothesis:
proc reg data=sashelp.class plots=none;
model weight = height;
H4: test height=4; /* F test for H0: b1=4 */
run;
quit;
I'm not sure that this is an answer to the original question, but...to obtain estimates of intercepts and slopes for both regressions (without algebra or ESTIMATE statements) and an easy way to test whether slopes are equal; plus testing slope equal to a particular value:
/* Fit reparameterized ANCOVA model that directly provides estimates of intercepts and slopes. Note use of NOINT in combination with different fixed effects terms. */ proc glimmix data=comp; class year; model y = year x*year / noint solution; estimate "Slope comparison 1YR versus 2YR" x*year 1 -1; store out=comp_model; run; /* Test hypotheses that a particular slope is equal to a particular value */ proc plm restore=comp_model; estimate "1YR slope= 0" x*year 1 / testvalue= 0; /* compare to solution output in model above */ estimate "1YR slope= -3" x*year 1 / testvalue= -3; run;
(I got the PLM tip from Kathleen Kiernan at SAS.)
Many thanks to Rick and SLD
I was wondering where I can find more info. on the use of Proc glimix and
Proc plm restore comands
I mean paricularity of their usages in experiment setting and analysis
Here are some resource ideas:
1. www.lexjansen.com provides a fabulously easy way to search all of the SAS user group proceedings, including SGF. Try "plm" or "glimmix" in the search window.
2. https://www.sas.com/store/books/categories/usage-and-reference/sas-for-mixed-models-second-edition/p... uses MIXED primarily, but the concepts and usage can be extended to GLIMMIX. The 3rd ed http://support.sas.com/publishing/authors/stroup.html is due out later this year and will feature lots of GLIMMIX.
3. https://www.crcpress.com/Generalized-Linear-Mixed-Models-Modern-Concepts-Methods-and-Applications/St... by Walt Stroup
Thanks
SLD
You are great ..
Javad
You are welcome 🙂
Yes, this is a very old post, and I don't want to open it for further discussion. The thread discusses several different models and goals and also contains some mistakes. If you want to understand how to formulate an ESTIMATE statement, see http://support.sas.com/kb/38/384.html
If you have questions that are not covered in the SAS KB article, feel free to open a new thread and post your code, model, and sample data.
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