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mksas33
Calcite | Level 5

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I have a data set which displays a "lognormal" shaped dependence of Y on X. The data is radioactive emission rate as a function of time. I see a rapid rise in the early stages followed by a slower decay over time.

 

The code I use is as follows:

 

proc glimmix data = QUERY_FOR_SUB1CT;

model rate = time / dist=lognormal link=log noscale solution;

run;

I found this code in an example in the communities. My question is how do I translate the results into a function that I can use in another program such as Excel. My parameter estimates are:

 

 

Parameter Estimates

Effect

Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-17.2289

65.7665

29249

-0.26

0.7933

time

-0.00013

0

29249

-Infty

<.0001

Scale

11.9519

0.09883

.

.

.

 

I see on Wikipedia that the lognormal pdf is as attached in the pic but I fail to see how to populate this equation given the SAS output.

 

1 ACCEPTED SOLUTION

Accepted Solutions
Rick_SAS
SAS Super FREQ

Are you sure that you want to use LINK=LOG? 

 

To model lognormal data, most people use only DIST=LOGNORMAL and an identity link function.The assumption is that

LOG(rate) is normally distributed and is estimated by 

LOG(RATE) = -17.23 - 0.00013*Time + eps

where eps (the residuals) is normally distributed with a variance that is estimated by the scale parameter.

View solution in original post

2 REPLIES 2
Rick_SAS
SAS Super FREQ

Are you sure that you want to use LINK=LOG? 

 

To model lognormal data, most people use only DIST=LOGNORMAL and an identity link function.The assumption is that

LOG(rate) is normally distributed and is estimated by 

LOG(RATE) = -17.23 - 0.00013*Time + eps

where eps (the residuals) is normally distributed with a variance that is estimated by the scale parameter.

mksas33
Calcite | Level 5

You are correct. I forgot to alter my code in what I posted above. On my machine I am using an identity link, such that results appear as follows.

 

Parameter Estimates

Effect

Estimate

Standard
Error

DF

t Value

Pr > |t|

Intercept

-2.7970

0.01497

29249

-186.85

<.0001

time

-0.00124

0.000120

29249

-10.28

<.0001

Scale

3.5190

0.02910

.

.

.

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