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How To Design And Report Experiments


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How To Design And Report Experiments


Over the years, I have been in a fortunate position of being asked to review a very large number of books. These have included contributions on a number of areas. As well as the usual research- focused references, I have been asked to review autobiographical and historical works. Generally speaking, books of the latter category are the easiest read and contrast with the books on the topic of designing and reporting experiments.


While many books look at the fundamentals of doing successful experiments and include good coverage of statistical techniques, this book very importantly considers the process in chronological order with specific attention given to effective design in the context of likely methods needed and expected results. Without full assessment of these aspects, the experience and results may not end up being as positive as one might have hoped. Ample coverage is then also provided of statistical data analysis, a hazardous journey in itself, and the reporting of findings, with numerous examples and helpful tips of common downfalls throughout.


I strongly recommend this book. The all-important steps of defining the research question and choosing an appropriate method are clearly written by these experienced authors and by doing so provide a framework, which if followed, would avoid many of the common difficulties encountered by those in training. The book is a succinct, clear, and readable treatise on this extremely important area. It should prove to be invaluable to researchers, practicing social scientists, students and anyone involved in the design and reporting of experiments Social Psychological Review


How to Design and Report Experiments is the perfect textbook and guide to the often bewildering world of experimental design and statistics. It provides a complete map of the entire process beginning with how to get ideas about research, how to refine your research question and the actual design of the experiment, leading on to statistical procedure and assistance with writing up of results.


For scientific, ethical and economic reasons, experiments involving animals should be appropriately designed, correctly analysed and transparently reported. This increases the scientific validity of the results, and maximises the knowledge gained from each experiment. A minimum amount of relevant information must be included in scientific publications to ensure that the methods and results of a study can be reviewed, analysed and repeated. Omitting essential information can raise scientific and ethical concerns. We report the findings of a systematic survey of reporting, experimental design and statistical analysis in published biomedical research using laboratory animals. Medline and EMBASE were searched for studies reporting research on live rats, mice and non-human primates carried out in UK and US publicly funded research establishments. Detailed information was collected from 271 publications, about the objective or hypothesis of the study, the number, sex, age and/or weight of animals used, and experimental and statistical methods. Only 59% of the studies stated the hypothesis or objective of the study and the number and characteristics of the animals used. Appropriate and efficient experimental design is a critical component of high-quality science. Most of the papers surveyed did not use randomisation (87%) or blinding (86%), to reduce bias in animal selection and outcome assessment. Only 70% of the publications that used statistical methods described their methods and presented the results with a measure of error or variability. This survey has identified a number of issues that need to be addressed in order to improve experimental design and reporting in publications describing research using animals. Scientific publication is a powerful and important source of information; the authors of scientific publications therefore have a responsibility to describe their methods and results comprehensively, accurately and transparently, and peer reviewers and journal editors share the responsibility to ensure that published studies fulfil these criteria.


Funding: This survey was co-funded by the National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) and the National Institutes for Health/Office of Laboratory Animal Welfare (NIH/OLAW)( ). NIH/OLAW had no role in study design, data collection and analysis, or preparation of the manuscript. Members of the NC3Rs Experimental Design Working Group (EDWG; independent, unpaid experts in experimental design and statistics) designed the survey. The NC3Rs paid independent Information Specialists to search published databases, and two independent statisticians Nick Parsons and Ed Kadyszewski to collect and analyse the data. The data were also analysed, and the manuscript prepared and submitted, by the NC3Rs (Carol Kilkenny) in consultation with members of the EDWG.


Competing interests: Dr Michael Festing was a member of the NC3Rs Board from September 2004 to July 2007. Members of the NC3Rs board are not remunerated. In addition Dr Festing would like to declare that he teaches short courses on the design and statistical analysis of animal experiments to scientists who are applicants for Home Office licences, for which he is paid. There are no competing interests for any of the other authors.


Scientific progress is driven by developing and testing novel hypotheses. Investigating these new ideas using appropriately and robustly designed experiments is fundamental to this process. The entire scientific community is also equally reliant on published research being transparently and accurately reported. Critical appraisal of scientific publications, for instance by peer review, is only possible if the methods and results of the studies are comprehensively reported. Accurate and transparent reporting is therefore vital to allow the reader to assess the methods of the study, and the reliability and importance of the scientific findings. This is particularly necessary for scientific research using animals, as poorly designed experiments and reporting omissions can raise both ethical and scientific concerns.


The National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), established by the UK government in 2004, is an independent scientific organisation dedicated to finding innovative solutions to replace animals in research with non-animal alternatives, reduce the number of animals used in experiments, and minimise suffering and improve animal welfare by refining husbandry and procedures (the 3Rs). It is widely accepted that applying the 3Rs to experiments using animals is consonant with good scientific practice [1], [2]. Well designed experiments using sufficient animals to achieve a scientific objective, together with an appropriate statistical analysis, enable researchers to increase the robustness and validity of their experimental results, maximising the knowledge gained from each experiment whilst minimising the number of animals used.


In order to assess the scope for improved experimental design, statistical analysis and reporting, and to further the implementation of the 3Rs, the NC3Rs has carried out a systematic survey of the quality of reporting, experimental design and statistical analysis of recently published biomedical research using laboratory animals. This paper reports the main findings and conclusions of this survey.


The main experiment reported in each publication was identified and detailed information was collected on objective measures such as the numbers and characteristics of the animals used including the species, strain, age, sex, and weight. Details of the experimental design such as the size and number of experimental groups, how animals were assigned to experimental groups, how experimental outcomes were assessed, what statistical and analytical methods were used, were also recorded. This information was collected in two distinct stages. In phase 1, data were collected from all 271 papers, and in phase 2, a random sub-sample of 48 papers (stratified by animal and by country of origin; i.e. 8 papers3 species2 countries) was chosen from the 271 papers evaluated in phase 1, and assessed in more detail (see Methods). The majority of results reported here were based on the complete sample of 271 papers; where this was not the case the sample number is indicated in the text.


The survey's first question addressed the fundamental premise of each scientific publication. A clear statement of the objective of the study, or the main hypothesis being tested, was described in the introduction by 95% of the 271 publications; the remaining 5% of the studies either did not describe the purpose of the study at all, or it was not clear to the assessors (see Table 3). In 6% of all 271 studies surveyed it was unclear whether one, or more than one, experiment was being described (see Table 4). The experimental unit (e.g. a single animal or a group of animals) was not clearly identified in 13% of the 48 studies assessed in more detail (phase 2) (see Table 5). The species (in the case of primates) or strain of animal used was reported by 99% of all 271 studies assessed (see Table 6), with 74% of all studies reporting the sex of the animals (see Table 7). Only 43% of all 271 studies reported the age of the animals and 46% reported their weight; some papers reported both weight and age (13%), whilst 24% reported neither (see Table 8).


In 4% of the 271 included publications, the number of animals used in the main experiment assessed was not reported anywhere in the methods or the results sections (see Table 9). None of the 48 studies assessed in more detail that did report animal numbers, discussed how the sample size was chosen (see Table 10). In 35% (69/198) of the papers that reported animal numbers in the methods section, the number of animals was either not reported in the results section, was unclear, or was different from that reported in the methods. In the majority of cases the number of animals reported in the results section was larger than in the methods section although in some papers the reverse was true (see Table 11). 59ce067264






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