1. Study design The experimental unit (e.g. a single animal, litter, or cage of animals). explanation

Within a design, biological and technical factors will often be organised hierarchically, such as cells within animals and mitochondria within cells, or cages within rooms and animals within cages. Such hierarchies can make determining the sample size difficult (is it the number of animals, cells or mitochondria?). The sample size is the number of experimental units per group. The experimental unit is defined as the biological entity subjected to an intervention independently of all other units, such that it is possible to assign any two experimental units to different treatment groups. It is also sometimes called the unit of randomisation. In addition, the experimental units should not influence each other on the outcomes that are measured.

Commonly, the experimental unit is the individual animal, each independently allocated to a treatment group (e.g. a drug administered by injection). However, the experimental unit may be the cage or the litter (e.g. a diet administered to a whole cage, or a treatment administered to a dam and investigated in her pups), or it could be part of the animal (e.g. different drug treatments applied topically to distinct body regions of the same animal). Animals may also serve as their own controls receiving different treatments separated by washout periods; here the experimental unit is an animal for a period of time. There may also be multiple experimental units in a single experiment, such as when a treatment is given to a pregnant dam and then the weaned pups are allocated to different diets [1]. See [2-4] for further guidance on identifying experimental units.  

Conflating experimental units with subsamples or repeated measurements can lead to artificial inflation of the sample size. For example, measurements from 50 individual cells from a single mouse represent n = 1 when the experimental unit is the mouse. The 50 measurements are subsamples and provide an estimate of measurement error so should be averaged or used in a nested analysis. Reporting n = 50 in this case is an example of pseudoreplication [5]. It underestimates the true variability in a study, which can lead to false positives and invalidate the analysis and resulting conclusions [5,6]. If, however, each cell taken from the mouse is then randomly allocated to different treatments and assessed individually, the cell might be regarded as the experimental unit.

Clearly indicate the experimental unit for each experiment so that the sample sizes and statistical analyses can be properly evaluated.

References

1. Burdge GC, Lillycrop KA, Jackson AA, Gluckman PD and Hanson MA (2008). The nature of the growth pattern and of the metabolic response to fasting in the rat are dependent upon the dietary protein and folic acid intakes of their pregnant dams and post-weaning fat consumption. Br J Nutr. doi: 10.1017/S0007114507815819
2. Bate ST and Clark RA (2014). The design and statistical analysis of animal experiments. Cambridge University Press. https://www.cambridge.org/core/books/design-and-statistical-analysis-of-animal-experiments/BDD758F3C49CF5BEB160A9C54ED48706
3. Lazic SE, Clarke-Williams CJ and Munafò MR (2018). What exactly is ‘N’ in cell culture and animal experiments? PLOS Biology. doi: 10.1371/journal.pbio.2005282
4. NC3Rs Experimental unit. (Access Date: 21/03/2019). Available at: https://eda.nc3rs.org.uk/experimental-design-unit
5.  Lazic SE (2010). The problem of pseudoreplication in neuroscientific studies: is it affecting your analysis? BMC Neuroscience. doi: 10.1186/1471-2202-11-5
6. Hurlbert SH (1984). Pseudoreplication and the design of ecological field experiments. Ecological Monographs. doi: 10.2307/1942661