statistical models

[always-good]

Hello everyone,  Please I need an urgent answer!

I have a table from an experiment in which, we tested the effect of the season ( winter: conducted in November and December) and summer: conducted in July and August) on the milk production of two groups of animals reared in the same conditions. Each group is randomly assigned according to season winter (30 animals) and summer(30 animals). Both groups have the same characteristics of animals(age, weight..), so can only test the effect of season. The results are presented in the table below :

My question is which one of the two suggested models is better describing the result;

1/ Mixed model for repeated measurements where y (milk yield)= µ+Cow+Season+samling time+Season*sampling time+error;

2/One-way Anova where y= µ+season+error

Please, I'm counting on the SAS community! 

	winter (Nov-Dec)	summer (July-Augst)	SEM	P
Milk yield
Fat
protein

[sbxkoenk]

Just FYI (everybody).

This is a duplicate of

statistical models

https://communities.sas.com/t5/New-SAS-User/statistical-models/m-p/887896

, but now posted on STAT-board.

The original post is from last Friday (we are Wednesday now).

Koen

[SteveDenham]

The two models enable you to test different things, so it boils down to what your experimental question is. If you are only interested in the effect of season, model 2 is appropriate. If you are interested in what the lactation curve looks like and whether there are differences between seasons at various sampling times, then the first model is appropriate. Note that the first model is a split-plot in time, with the whole plot being exactly what model 1 tests (at least for balanced data).  I would recommend finding a copy of SAS for Mixed Models (any edition, but the third edition is best), and particularly Chapter 8: Analysis of Repeated Measures Data for more information.

SteveDenham

[always-good]

Thanks a lot for your rsponse!