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Department of Animal Science, Michigan State University, East Lansing 48824-1225
2 Corresponding author: tempelma{at}msu.edu
Because of increasing constraints placed on conducting large studies at universities, more research is being conducted on commercial dairies, thereby raising some implications for experimental designs and data analysis. For example, experimental units are often specified to be pens of animals in on-farm studies, thereby requiring that at least 2 pens be used per treatment group in a single-dairy study. Even when treatments are compared within pens, the precision of inference on treatment differences is still primarily limited by the number of pens in the study, rather than the number of cows per treatment in each pen. Other challenges with on-farm studies include proper blocking and randomization of cows or pens to treatments. On the other hand, multiple farm studies are attractive, because they facilitate a broader scope of inference on treatment effects across a wider range of management or climatic conditions and genetic backgrounds compared with single-site university studies. Furthermore, studies based on multiple farms or multiple pens within a single large farm can facilitate greater power for treatment comparisons on binary reproduction or health responses than can be achieved at a smaller research herd. Because quantitative geneticists have been analyzing commercial dairy data for decades, they have developed useful data analysis techniques that should be harnessed to facilitate even greater statistical scope and power for on-farm studies.
Key Words: experimental design • experimental unit • scope of inference
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