Repeated Measures Analysis and Some Experimental Design Considerations in Animal Science

Repeated measurements, as the name suggests, are observations of the same characteristic, which are made several times. What distinguishes such observations from those in more traditional statistical data modeling is that the same variable is measured on the same observational unit more than once. The responses are not independent as in the usual regression analysis and more than one observational unit is involved. The responses do not form a simple time series. To many animal scientists, a mention of the term, repeated measurements evokes the idea either of the fisheries study of growth curves or split plot designs. However, once one begins to delve into the subject, one realizes that these two subjects, in no way, completely cover the field of repeated observations. In fact, repeated measurements are very frequent not only in animal science experiments but also in almost all scientific fields where statistical models are used [1].

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Figure 1. Repeated measures analysis diagram in SPSS package. (a) data input box, (b) repeated measures analyze paths, (c) repeated measures define factor(s) dialog box, (d) repeated measures dialog box Factors Box BSF box Covariates box