Codes for cytokine expression data

[Agbee]

I am looking for codes to run data for cytokine expression. I had two groups of pigs 6 each and got blood from them (day 0 and day 14). I run the results with proc mixed and they were not normally distributed. Anyone with an idea on how to run it. I'll appreciate if I get the codes too.

[ballardw]

Many users here don't want to download Excel files because of virus potential, others have such things blocked by security software. Also if you give us Excel we have to create a SAS data set and due to the non-existent constraints on Excel data cells the result we end up with may not have variables of the same type (numeric or character) and even values.

Instructions here: https://communities.sas.com/t5/SAS-Communities-Library/How-to-create-a-data-step-version-of-your-dat... will show how to turn an existing SAS data set into data step code that can be pasted into a forum code box using the <> icon or attached as text to show exactly what you have and that we can test code against.

And as minimum you could include the Proc Mixed code you actually used so we have some idea what you did.

Is there supposed to be a guarantee that the results should be normally distributed?

[dekstone3]

Thanks for the response and suggestion. I am a new user so it'll take some time to figure things out. I will get the codes i have and post it. Regards!

[SteveDenham]

Here is a snippet from our protocols regarding analysis of cytokine data:

For cytokines, a repeated measures analysis (mixed model) will be conducted. For each endpoint, the model will test for the effects of treatment, time, and the interaction of treatment and time(1). A lognormal distribution will be assumed unless there are several values outside the range of quantitation, in which case a rank transformation will be applied. Ranks will be calculated across all timepoints, and the analysis will use the ANOVAF option and MIVQUE0 technique in SAS PROC MIXED(2) .

(1)Littell RC, Milliken GA, Stroup WW, Wolfinger RD. SAS System for Mixed Models. Cary (NC): SAS Institute Inc.; 1996.
(2)Brunner, E., Domhof, S., and Langer, F. Nonparametric Analysis of Longitudinal Data in Factorial Experiments, New York: John Wiley & Sons.; 2002.

We use PROC GLIMMIX, but you could get essentially the same analysis using PROC MIXED if you log transformed the data before analysis.  The code we use  is estimating the marginal effects, as there is only an R-side variance-covariance matrix being estimated.  Given that, PROC GEE or PROC GENMOD are also candidates. My gut feeling is that you would log transform the data before analysis rather than using a LOG link function, but I will defer to @StatDave for a better response than "a gut feeling".

SteveDenham

[dekstone3]

Thanks. This is helpful.

[StatDave]

If the response is positive and continuously valued, then gamma and inverse gaussian distributions are possible distributions for the model. Repeated measures data using either of these distributions can be modeled using a GEE model fit in either the GEE or GENMOD procedures. This is a population-averaged type of model. A subject-specific type of model using these distributions can be fit using a random effects model in PROC GLIMMIX.