Essential 10

1. Study Design

For each experiment, provide brief details of study design including:

The choice of control or comparator group is dependent on the experimental objective. Negative controls are used to determine if a difference between groups is caused by the intervention (e.g. wild-type animals vs genetically modified animals, placebo vs active treatment, sham surgery vs. surgical intervention). Positive controls can be used to support the interpretation of negative results or determine if an expected effect is detectable.  It may not be necessary to include a separate control with no active treatment if, for example, the experiment aims to compare a treatment administered by different methods (e.g. intraperitoneal administration vs. oral gavage), or animals that are used as their own control in a longitudinal study. A pilot study, such as one designed to test the feasibility of a procedure might also not require a control group.

For complex study designs, a visual representation is more easily interpreted than a text description, so a timeline diagram or flow chart is recommended. Diagrams facilitate the identification of which treatments and procedures were applied to specific animals or groups of animals, and at what point in the study these were performed. They also help to communicate complex design features such as whether factors are crossed or nested (hierarchical/multi-level designs), blocking (to reduce unwanted variation, see item 4 – Randomisation), or repeated measurements over time on the same experimental unit (repeated measures designs), see [1-3] for more information on different design types. The Experimental Design Assistant (EDA) is a platform to support researchers in the design of in vivo experiments, it can be used to generate diagrams to represent any type of experimental design [4].

For each experiment performed, clearly report all groups used. Selectively excluding some experimental groups (for example because the data are inconsistent, or conflict with the narrative of the paper) is misleading and should be avoided [5]. Ensure that test groups, comparators and controls (negative or positive) can be identified easily. State clearly if the same control group was used for multiple experiments, or if no control group was used. 



  1. Festing MF and Altman DG (2002). Guidelines for the design and statistical analysis of experiments using laboratory animals. ILAR journal.
  2. Bate ST and Clark RA (2014). The design and statistical analysis of animal experiments. Cambridge University Press.
  3. Ruxton G and Colegrave N (2017). Experimental design for the life sciences. Fourth Edition. Oxford University Press.
  4. Percie du Sert N, Bamsey I, Bate ST, Berdoy M, Clark RA, Cuthill I, Fry D, Karp NA, Macleod M, Moon L, Stanford SC and Lings B (2017). The Experimental Design Assistant. PLoS Biol. doi: 10.1371/journal.pbio.2003779
  5. The BMJ Scientific misconduct. (Access Date: 10 january 2020). Available at:

Example 1 

“The DAV1 study is a one-way, two-period crossover trial with 16 piglets receiving amoxicillin and placebo at period 1 and only amoxicillin at period 2. Amoxicillin was administered orally with a single dose of 30 Plasma amoxicillin concentrations were collected at same sampling times at each period: 0.5, 1, 1.5, 2, 4, 6, 8, 10 and 12 h..” [1]

Example 2 

Example of a study plan created using the Experimental Design Assistant

“Example of a study plan created using the Experimental Design Assistant showing a simple comparative study for the effect of two drugs on the metastatic spread of two different cancer cell lines. Block randomisation has been used to create 3 groups containing an equal number of zebrafish embryos injected with either cell line, and each group will be treated with a different drug treatment (including vehicle control). Each measurement outcome will be analysed by 2-way ANOVA to determine the effect of drug treatment on growth, survival and invasion of each cancer cell line.” [2]


  1. Nguyen TT, Bazzoli C and Mentre F (2012). Design evaluation and optimisation in crossover pharmacokinetic studies analysed by nonlinear mixed effects models. Statistics in medicine. doi: 10.1002/sim.4390
  2. Hill D, Chen L, Snaar-Jagalska E and Chaudhry B (2018). Embryonic zebrafish xenograft assay of human cancer metastasis [version 2; referees: 2 approved]. F1000Research. doi: 10.12688/f1000research.16659.2


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.



  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.
  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:
  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

Example 1 

 “The present study used the tissues collected at E15.5 from dams fed the 1X choline and 4X choline diets (n = 3 dams per group, per fetal sex; total n = 12 dams). To ensure statistical independence, only one placenta (either male or female) from each dam was used for each experiment. Each placenta, therefore, was considered to be an experimental unit.” [1] 

Example 2 

“We have used data collected from high-throughput phenotyping, which is based on a pipeline concept where a mouse is characterized by a series of standardized and validated tests underpinned by standard operating procedures (SOPs)…The individual mouse was considered the experimental unit within the studies.” [2] 

Example 3 

“Fish were divided in two groups according to weight (0.7-1.2 g and 1.3-1.7 g) and randomly stocked (at a density of 15 fish per experimental unit) in 24 plastic tanks holding 60 L of water.” [3] 

Example 4 

“In the study, n refers to number of animals, with five acquisitions from each [corticostriatal] slice, with a maximum of three slices obtained from each experimental animal used for each protocol (six animals each group).” [4]



  1. Kwan S, King J, Grenier J, Yan J, Jiang X, Roberson M and Caudill M (2018). Maternal Choline Supplementation during Normal Murine Pregnancy Alters the Placental Epigenome: Results of an Exploratory Study. Nutrients. doi: 10.3390/nu10040417
  2. Karp NA, Mason J, Beaudet AL, Benjamini Y, Bower L, Braun RE, Brown SDM, Chesler EJ, Dickinson ME, Flenniken AM, Fuchs H, Angelis MHd, Gao X, Guo S, Greenaway S, Heller R, Herault Y, Justice MJ, Kurbatova N, Lelliott CJ, Lloyd KCK, Mallon A-M, Mank JE, Masuya H, McKerlie C, Meehan TF, Mott RF, Murray SA, Parkinson H, Ramirez-Solis R, et al. (2017). Prevalence of sexual dimorphism in mammalian phenotypic traits. Nature communications. doi: 10.1038/ncomms15475
  3. Ribeiro FdAS, Vasquez LA, Fernandes JBK and Sakomura NK (2012). Feeding level and frequency for freshwater angelfish. Revista Brasileira de Zootecnia. doi: 10.1590/S1516-35982012000600033 
  4. Grasselli G, Rossi S, Musella A, Gentile A, Loizzo S, Muzio L, Di Sanza C, Errico F, Musumeci G, Haji N, Fresegna D, Sepman H, De Chiara V, Furlan R, Martino G, Usiello A, Mandolesi G and Centonze D (2013). Abnormal NMDA receptor function exacerbates experimental autoimmune encephalomyelitis. Br J Pharmacol. doi: 10.1111/j.1476-5381.2012.02178.x