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SAS PROC MIXED and JMP Random Effect Variance Estimation are Different

Anastasia

New Contributor

Joined:

Dec 19, 2016

1 ACCEPTED SOLUTION

Accepted Solutions
jiancao

Staff

Joined:

Jul 7, 2014

Solution

The difference you observed is caused by the Kackar-Harville correction applied by SAS Proc Mixed when the DDFM=KENWARDROGER option is set. JMP doesn’t apply this adjustment to the BLUP standard errors. For details, please see http://www.jmp.com/support/help/13/The_Kackar-Harville_Correction.shtml#1502602 

To get the same results, replace DDFM=KENWARDROGER with DDFM=SATTERTHWAITE in your SAS code.

5 REPLIES
Anastasia

New Contributor

Joined:

Dec 19, 2016

Dear All,

 

I am trying to compare the results of SAS PROC Mixed and JMP mixed model. I thought the results would be the same, but they are not. I hope JMP can give the same results of SAS PROC MIXED. Could anyone help me with it?

 

My SAS code as following:

proc mixed data=Data;

class sample;

model result= time / DDFM=KENWARDROGER s cl E3 alphap=0.05 residual outp=mixedout;

random sample /s;

ods output SolutionF=F SolutionR=Ran ;

run;

 

The results for the fixed effect are

 

Effect

Estimate

Standard Error

DF

t Value

Pr > |t|

Alpha

Lower

Upper

Intercept

7.2638

0.197

15.4

36.86

<.0001

0.05

6.8449

7.6828

time

-0.4636

0.0615

14

-7.54

<.0001

0.05

-0.5955

-0.3317

 

The results for the random effect are:

 

Effect

lot

Estimate

Std Err Pred

DF

t Value

Pr > |t|

sample

1

-0.01193

0.1762

4.95

-0.07

0.9487

sample

2

0.1647

0.1762

4.95

0.93

0.3932

sample

3

-0.2869

0.1762

4.95

-1.63

0.165

sample

4

0.1799

0.1762

4.95

1.02

0.3546

sample

5

-0.04579

0.1762

4.95

-0.26

0.8055

 

 

 

Then, I used JMP's interface to generate the following code:

 

DATA Data1; INPUT time sample result; Lines;

1 1 7.04755019105043

2 1 5.84207852539687

3 1 6.02392278004353

4 1 5.43660061149986

1 2 7.27729854732895

2 2 6.5688837201289

3 2 5.6460380590458

4 2 5.88401060914374

1 3 6.15741854776455

2 3 5.90111584525169

3 3 5.78059226421567

4 3 4.91383166620419

1 4 6.98283726578696

2 4 6.3260371191925

3 4 6.09507016140813

4 4 6.06037720591234

1 5 6.95244413898138

2 5 6.36002369549625

3 5 5.94090548712508

4 5 4.9001077313589

;

RUN;

 

PROC MIXED ASYCOV DATA=Data1 ALPHA=0.05;

CLASS sample;

MODEL result = time/ SOLUTION DDFM=KENWARDROGER;

RANDOM sample / SOLUTION ;

RUN;

 

I got:

 

Parameter Estimates

Term

 

Estimate

Std Error

DFDen

t Ratio

Prob>|t|

Intercept

 

7.2638308

0.197046

15.45

36.86

<.0001*

time

 

-0.463589

0.061501

14

-7.54

<.0001*

 

Random Effect Predictions

Term

 

BLUP

Std Error

DFDen

t Ratio

Prob>|t|

sample[1]

 

-0.011928

0.153244

4.948

-0.08

0.9410

sample[2]

 

0.1647348

0.153244

4.948

1.07

0.3320

sample[3]

 

-0.28692

0.153244

4.948

-1.87

0.1207

sample[4]

 

0.1799016

0.153244

4.948

1.17

0.2938

sample[5]

 

-0.045789

0.153244

4.948

-0.30

0.7772

 

 

It seems like Std error estimates for random effects are not the same in JMP and SAS. I am wondering if there is anyone know how could I code the JMP to make it is the same results as SAS.

 

Thank you very much,

 

Anastasia

markbailey

Staff

Joined:

Jun 23, 2011

I think that this kind of question is best served by support@jmp.com. They are very friendly, almost as friendly as the people here!

jiancao

Staff

Joined:

Jul 7, 2014

Solution

The difference you observed is caused by the Kackar-Harville correction applied by SAS Proc Mixed when the DDFM=KENWARDROGER option is set. JMP doesn’t apply this adjustment to the BLUP standard errors. For details, please see http://www.jmp.com/support/help/13/The_Kackar-Harville_Correction.shtml#1502602 

To get the same results, replace DDFM=KENWARDROGER with DDFM=SATTERTHWAITE in your SAS code.

dr_winfried_koc

Community Trekker

Joined:

Nov 5, 2014

Thanks for clarification.

I work in environments where both SAS and JMP are in use; therefore I appreciate consistency between both. In case where certain differences are intended by SAS Institute, these should always be indicated in the documentation.

Anastasia

New Contributor

Joined:

Dec 19, 2016

Thank you very much. It works.