topic Re: Interpreting/translating glimmix output into a formula for use in Excel or other programs in SAS Programming

Interpreting/translating glimmix output into a formula for use in Excel or other programs

mksas33 — Thu, 16 Nov 2017 15:01:54 GMT

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.

Re: Interpreting/translating glimmix output into a formula for use in Excel or other programs

Rick_SAS — Thu, 16 Nov 2017 15:23:51 GMT

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.

Re: Interpreting/translating glimmix output into a formula for use in Excel or other programs

mksas33 — Thu, 16 Nov 2017 15:29:59 GMT

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	.	.	.