10-14-2019
ojibous
Calcite | Level 5
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10-11-2019
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Latest posts by ojibous
Subject Views Posted 1855 10-12-2019 11:18 AM 884 10-11-2019 03:16 PM 1898 10-11-2019 02:45 PM 1914 10-11-2019 02:11 PM 1947 10-11-2019 01:31 PM 1968 10-11-2019 01:13 PM 1971 10-11-2019 01:08 PM 1982 10-11-2019 12:57 PM -
Activity Feed for ojibous
- Posted Re: PROC NLMIXED: Execution error for observation 2501 on Statistical Procedures. 10-12-2019 11:18 AM
- Posted Convert code from proc Logistic to NLIN or NLIMIXED on Statistical Procedures. 10-11-2019 03:16 PM
- Posted Re: PROC NLMIXED: Execution error for observation 2501 on Statistical Procedures. 10-11-2019 02:45 PM
- Posted Re: PROC NLMIXED: Execution error for observation 2501 on Statistical Procedures. 10-11-2019 02:11 PM
- Posted Re: PROC NLMIXED: Execution error for observation 2501 on Statistical Procedures. 10-11-2019 01:31 PM
- Posted Re: PROC NLMIXED: Execution error for observation 2501 on Statistical Procedures. 10-11-2019 01:13 PM
- Posted Re: PROC NLMIXED: Execution error for observation 2501 on Statistical Procedures. 10-11-2019 01:08 PM
- Posted PROC NLMIXED: Execution error for observation 2501 on Statistical Procedures. 10-11-2019 12:57 PM
10-12-2019
11:18 AM
Thank you Paige. That's exactly what I did. Thank you for validating it. Thank you for your time too
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10-11-2019
03:16 PM
Hello,
Please I would love to run this logistic procedure with proc nlin or proc nlimixed, any ideas please? the codes I tried are below. Thanks
proc logistic data = rsm1;
model edema (event="1") = DoseA DoseT DoseA*DoseT DoseA*DoseA DoseT*DoseT/link = probit;
output out=pred p=prob;
run;
**This did not work
proc nlmixed data = rsm1; call streaminit(123456);
parms beta0=1 beta1=1 beta2=1 beta11=1 beta12=1 beta22=1 s2=1;
y2 = (beta0 + beta1*DoseA + beta2*DoseT + beta11*DoseA*DoseA
+ beta22*DoseT*DoseT + beta12*DoseA*DoseT);
p = exp(y2)/(1+exp(y2));
model Edema~binary(p);
predict y2 out=y2;
run;
**I'm not getting same results with this:
proc nlin data =rsm1 method=newton;
parms beta0=1 beta1=1 beta2=1 beta11=1 beta12=1 beta22=1;
y2 = (beta0 + beta1*DoseA + beta2*DoseT + beta11*DoseA*DoseA
+ beta22*DoseT*DoseT + beta12*DoseA*DoseT);
p = probnorm(edema);
if (edema = 1) then p = 1-p;
model p=y2;
output out=p p=predict;
run;
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10-11-2019
02:45 PM
Okay. I'm sorry I think I threw many information without explaining. This is my task: 1. Find the dose of A & T that has the optimum response of change in blood pressure (cdbp - continuous variable) (which I already did) 2. Find the dose of A & T that that has the highest probability of the side effect: edema.(binary variable) (Where I am presently). 3. Maximize the change in blood pressure while minimizing the probability of side effect edema. In the end I want to produce a surface plot for (1) and (2) and compare them both. Or if possible, overlay the surface plots. Any advise on SAS procedures valuable will be appreciated.
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10-11-2019
02:11 PM
Okay. Thank you so much Paige. I would try that. It is a good start. My end goal is to condition for binary response while maximizing for the continuous response. I think that's what took me to PROC NLIN and NLMIXED.
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10-11-2019
01:31 PM
Thank you for responding Paige. I would have used PROC logistic but my model is quadratic. I'm not sure if Logistic can do that. PROC RSREG would work fine too if my response variable was continuous. But now it is binary. I am trying to find the combination that will produce the optimum response. PROC NLMIXED worked perfectly fine when my response was continuous, using the code below. But now I want to do same with a binary response. proc nlmixed data = rsm1 tech=newrap; parms beta0=1 beta1=1 beta2=1 beta11=1 beta12=1 beta22=1 s2=1; y = (beta0 + beta1*DoseA + beta2*DoseT + beta11*DoseA*DoseA + beta22*DoseT*DoseT + beta12*DoseA*DoseT); model cdbp~normal(y,s2); predict y out=y; run; Thanks
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10-11-2019
01:13 PM
I am also trying to see if Proc NLIN can do same thing but with probit; but I am stuck at the model part. Can you help with my codes? proc nlin data =rsm1 method=newton; parms beta0=1 beta1=1 beta2=1 beta11=1 beta12=1 beta22=1 s2=1; y2 = (beta0 + beta1*DoseA + beta2*DoseT + beta11*DoseA*DoseA + beta22*DoseT*DoseT + beta12*DoseA*DoseT); p = probnorm(y2); if (edema = 1) then p = 1-p; model.edema = p; output out=p p=predict; run;
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10-11-2019
01:08 PM
Yes I did that. I don't see anything wrong or unusual.
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10-11-2019
12:57 PM
Hello, Please I am trying to run these codes but I'm getting the above errors and do not know what to do. I will appreciate if anyone can help me. Thanks There are 8000 observations. Edema (Yes=1/No=0) proc nlmixed data = rsm1; call streaminit(12345); parms beta0=1 beta1=1 beta2=1 beta11=1 beta12=1 beta22=1 s2=1; y2 = (beta0 + beta1*DoseA + beta2*DoseT + beta11*DoseA*DoseA + beta22*DoseT*DoseT + beta12*DoseA*DoseT); p = exp(y2)/(1+exp(y2)); model Edema~binary(p); predict y2 out=y2; run;
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