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For example, in cancer studies an animal might be dropped from the study and euthanised before the predetermined time point if the size of a subcutaneous tumour exceeds a specific volume. Criteria for excluding samples or data include failure to meet quality control standards, such as insufficient sample volumes, unacceptable levels of contaminants, poor histological quality, etc. Similarly, how the researcher will define and handle data outliers during the analysis should also be decided before the experiment starts (see item 3bfor guidance on responsible data cleaning).Įxclusion criteria may also reflect the ethical principles of a study in line with its humane endpoints (see item 16 – Animal care and monitoring). development of motor impairments that could affect behavioural measurements). task performance has to exceed a given threshold). In studies where selected data are re-analysed for a different purpose, inclusion and exclusion criteria should describe how data were selected.Įxclusion criteria may result from technical or welfare issues such as complications anticipated during surgery, or circumstances where test procedures might be compromised (e.g. body weights must be within a certain range for a particular procedure) or related to other study parameters (e.g. Inclusion criteria should not be confused with animal characteristics (see item 8 – Experimental animals) but can be related to these (e.g. Inclusion and exclusion criteria define the eligibility or disqualification of animals and data once the study has commenced. To ensure scientific rigour, the criteria should be defined before the experiment starts and data are collected.
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