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  3. The Design and Statistical Analysis of Animal Experiments
  • Cited by 73
Publisher:
Cambridge University Press
Online publication date:
March 2014
Print publication year:
2014
Online ISBN:
9781139344319
DOI:
https://doi.org/10.1017/CBO9781139344319
Subjects:
Animal Behaviour, Life Sciences, Quantitative Biology, Biostatistics and Mathematical Modeling
Information

Book description

Written for animal researchers, this book provides a comprehensive guide to the design and statistical analysis of animal experiments. It has long been recognised that the proper implementation of these techniques helps reduce the number of animals needed. By using real-life examples to make them more accessible, this book explains the statistical tools employed by practitioners. A wide range of design types are considered, including block, factorial, nested, cross-over, dose-escalation and repeated measures and techniques are introduced to analyse the experimental data generated. Each analysis technique is described in non-mathematical terms, helping readers without a statistical background to understand key techniques such as t-tests, ANOVA, repeated measures, analysis of covariance, multiple comparison tests, non-parametric and survival analysis. This is also the first text to describe technical aspects of InVivoStat, a powerful open-source software package developed by the authors to enable animal researchers to analyse their data and obtain informative results.

Reviews

'At last, a readable statistics book focusing solely on preclinical experimental designs, data and its analysis that should form part of an in-vivo scientist’s personal library. The author’s unique insight into the statistical needs of preclinical scientists has allowed them to compile a non-technical guide that can facilitate sound experimental design, meaningful data analysis and appropriate scientific conclusions. I would also encourage all readers to download and explore 'InVivoStat', a powerful software package that both my group and I use on a daily basis.'

Darrel J. Pemberton - Janssen Research and Development

'This book provides an indispensable reference for any in-vivo scientist. It addresses common pitfalls in animal experiments and provides tangible advice to address sources of bias, thus increasing the robustness of the data. … The text links experimental design and statistical analysis in a practical way, easily accessible without any prior statistical knowledge. The statistical concepts are described in plain English, avoiding overuse of mathematical formulas and illustrated with numerous examples relevant to biomedical scientists. … This book will help scientists improve the design of animal experiments and give them the confidence to use more complex designs, enabling more efficient use of animals and reducing the number of experimental animals needed overall.'

Nathalie Percie du Sert - National Centre for the Replacement, Refinement and Reduction of Animals in Research

'This book will transform the way biomedical scientists plan their work and interpret their results. Although the subject matter covers complex points, it is easy to read and packed with relevant examples. There are two particularly striking features. First, at no point do the authors resort to mathematical equations as a substitute for explaining the concepts. Secondly, they explain why the choice of experimental design is so important, why the design affects the statistical analysis and how to ensure the choice of the most appropriate statistical test. The final section describes how to use InvivoStat (a software package, assembled by the authors), which enables researchers to put into practice all the points covered in this book. This is an invaluable combination of resources that should be within easy reach of anyone carrying out experiments in the biomedical sciences, especially if their work involves using live animals.'

Clare Stanford - University College London

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Contents

Contents
References
References
Afsarinejad, K. (1983). Balanced repeated measurements designs. Biometrika, 70 CrossRef | Google Scholar(1), 199–204.
Anderson, V. L. and McLean, R. A. (1974). Design of Experiments. Marcel Dekker Inc. Google Scholar: New York.
Andreasen, J. T., Henningsen, K., Bate, S. T., Christiansen, S. and Wiborg, O. (2011). Nicotine reverses anhedonic-like response and cognitive impairment in the rat chronic mild stress model of depression: comparison with sertraline. Journal of Psychopharmacology, 25 CrossRef | Google Scholar | PubMed(8), 1134–41.
Armitage, P., Berry, G. and Matthews, J. N. S. (2002). Statistical Methods in Medical Research, 4th edition. Wiley-Blackwell CrossRef | Google Scholar: Malden, MA.
Aylott, M., Bate, S. T., Collins, S., Jarvis, P. and Saul, J. (2011). Review of the statistical analysis of the dog telemetry study. Pharmaceutical Statistics, 10 CrossRef | Google Scholar | PubMed(3), 236–49.
Bailey, R. A. (2008). Design of Comparative Experiments. Cambridge University Press CrossRef | Google Scholar: Cambridge, UK.
Bartlett, M. S. (1937). Properties of sufficiency and statistical tests. Proceedings of the Royal Statistical Society Series A – Mathematical and Physical Sciences, 160 CrossRef | Google Scholar(901), 268–82.
Barton, N. J., Strickland, I. T., Bond, S. M., et al. (2007). Pressure application measurement (PAM): a novel behavioural technique for measuring hypersensitivity in a rat model of joint pain. Journal of Neuroscience Methods, 163 CrossRef | Google Scholar(1), 67–75.
Bate, S. T. and Boxall, J. (2008). The construction of multi-factor crossover designs in animal husbandry studies. Pharmaceutical Statistics, 7 CrossRef | Google Scholar | PubMed(3), 179–94.
Bate, S. T. and Jones, B. (2008). A review of uniform cross-over designs. Journal of Statistical Planning and Inference, 138 CrossRef | Google Scholar(2), 336–51.
Belluzzi, J. D., Lee, A. G., Oliff, H. S. and Leslie, F. M. (2004). Age-dependent effects of nicotine on locomotor activity and conditioned place preference in rats. Psychopharmacology, 174 CrossRef | Google Scholar | PubMed, 389–95.
Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B, 57 Google Scholar, 289–300.
Bennett, C. M., Wolford, G. L. and Miller, M. B. (2009). The principled control of false positives in neuroimaging. Social Cognitive and Affective Neuroscience, 4 CrossRef | Google Scholar | PubMed(4), 417–22.
Bianchi, M. and Baulieu, E. E. (2012). 3β-methoxy-pregnenolone (MAP4343) as an innovative therapeutic approach for depressive disorders. Proceedings of the National Academy of Sciences, 109 CrossRef | Google Scholar | PubMed(5), 1713–18.
Biggers, J. D., Baskar, J. F. and Torchiana, D. F. (1981). Reduction of fertility of mice by the intrauterine injection of prostaglandin antagonists. Journal of Reproduction and Fertility, 63 CrossRef | Google Scholar | PubMed, 365–72.
Bison, S., Carboni, L., Arban, R., et al. (2009). Differential behavioral, physiological, and hormonal sensitivity to LPS challenge in rats. International Journal of Interferon, Cytokine and Mediator Research, 1 CrossRef | Google Scholar, 1–13.
Blakesley, R. E., Mazumdar, S., Dew, M. A., et al. (2009). Comparisons of methods for multiple hypothesis testing in neuropsychological research. Neuropsychology, 23 CrossRef | Google Scholar | PubMed(2), 255–64.
Bonferroni, C. E. (1936). Teoria statistica delle classi e calcolo delle probabilita. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commerciali di Firenze, 8 Google Scholar, 3–62.
Box, G. E. P. (1953). Non-normality and tests on variance. Biometrika, 40 CrossRef | Google Scholar(3/4), 318–35.
Boxall, J., Heath, S., Bate, S. and Brautigam, J. (2004). Modern concepts of socialisation for dogs: implications for their behaviour, welfare and use in scientific procedures. ATLA. Alternatives to Laboratory Animals, 32 Google Scholar | PubMed, 81–93.
Brammer, R. J. (2003). Modelling covariance structure in ascending dose studies of isolated tissues and organs. Pharmaceutical Statistics, 2 CrossRef | Google Scholar(2), 103–12.
Bright, J., Aylott, M., Bate, S., et al. (2011). Recommendations on the statistical analysis of the Comet assay. Pharmaceutical Statistics, 10 CrossRef | Google Scholar | PubMed(6), 485–93.
Brooks, K. J., Bunce, K. T., Hasse, M. V., et al. (2005). MRI quantification in vivo of corticosteroid induced thymus involution in mice: correlation with ex vivo measurements. Steroids, 70 CrossRef | Google Scholar | PubMed(4), 267–72.
Brown, M. B. and Forsythe, A. B. (1974). Robust tests for equality of variances. Journal of the American Statistical Society, 69 CrossRef | Google Scholar(346), 364–7.
Burden, R. L. and Faires, J. D. (2011). Numerical Analysis, 9th edition. Brooks/Cole Publishing: Pacific Grove, CA Google Scholar.
Button, K. S., Ioannidis, J. P., Mokrysz, C., et al. (2013). Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14 CrossRef | Google Scholar | PubMed, 365–76.
Chaves, A. A., Keller, W. J., O’Sullivan, S., et al. (2006). Cardiovascular monkey telemetry: sensitivity to detect QT interval prolongation. Journal of Pharmacological and Toxicological Methods, 54 CrossRef | Google Scholar | PubMed(2), 150–8.
Clark, R. A., Shoaib, M., Hewitt, K. N., Stanford, S. C. and Bate, S. T. (2012). A comparison of InVivoStat with other statistical software packages for analysis of data generated from animal experiments. Journal of Psychopharmacology, 26 CrossRef | Google Scholar | PubMed(8), 1136–42.
Clarke, G. M. and Kempson, R. E. (1997). Introduction to the Design and Analysis of Experiments. Arnold Google Scholar: London.
Cochran, W. G. and Cox, G. M. (1957). Experimental Designs, 2nd edition. Wiley & Sons, Inc. Google Scholar: New York, London.
Cohen, J. (1988). Statistical Power Analysis for the Behavioural Sciences Google Scholar, 2nd edition. Lawrence Erlbaum Associates: Hillsdale, NJ.
Crowder, M. J. and Hand, D. J. (1990). Analysis of Repeated Measures. Chapman and Hall/CRC: London Google Scholar.
Cumming, G., Fidler, F. and Vaux, D. L. (2007). Error bars in experimental biology. The Journal of Cell Biology, 177 CrossRef | Google Scholar | PubMed(1), 7–11.
Curran-Everett, D. (2000). Multiple comparisons: philosophies and illustrations. American Journal of Physiology – Regulatory, Integrative and Comparative Physiology, 279 CrossRef | Google Scholar | PubMed(1), R1–8.
Curtin, L. I., Grakowsky, J. A., Suarez, M., et al. (2009). Evaluation of buprenorphine in a postoperative pain model in rats. Comparative Medicine, 59 Google Scholar(1), 60–71.
Downie, D., Antipatis, C., Delday, M. I., Maltin, C. A. and Sneddon, A. A. (2005). Moderate maternal vitamin A deficiency alters myogenic regulatory protein expression and perinatal organ growth in the rat. American Journal of Physiology – Regulatory, Integrative and Comparative Physiology, 288 CrossRef | Google Scholar | PubMed(1), 73–9.
Dudchenko, P. A., Wood, E. R. and Eichenbraum, H. (2000). Neurotoxic hippocampal lesions have no effect on odor span and little effect on odor recognition memory but produce significant impairments on spatial span, recognition, and alteration. The Journal of Neuroscience, 20 CrossRef | Google Scholar(8), 2964–77.
Duncan, D. B. (1955). Multiple range and multiple F tests. Biometrics, 11 CrossRef | Google Scholar(1), 1–42.
Dunnett, C. W. (1955). A multiple comparison procedure for comparing several treatments with a control. Journal of the American Statistical Association, 50 CrossRef | Google Scholar(272), 1096–121.
Dunnett, C. W. (1964). New tables for multiple comparisons with a control. Biometrics, 20 CrossRef | Google Scholar(3), 482–91.
Elashoff, J. D. (1981). Down with multiple t-tests!Gastroenterology, 80 Google Scholar | PubMed, 615–20.
Festing, M. F. W. (1994). Reduction of animal use: experimental design and quality of experiments. Laboratory Animals, 28 CrossRef | Google Scholar(3), 212–21.
Festing, M. F. W. (2003a). Principles: the need for better experimental design. Trends in Pharmacological Sciences, 24 CrossRef | Google Scholar | PubMed(7), 341–5.
Festing, M. F. W. (2003b). We should be designing better experiments. Veterinary Anaesthesia and Analgesia, 30 CrossRef | Google Scholar | PubMed, 58–60.
Festing, M. F. W. and Altman, D. G. (2002). Guidelines for the design and statistical analysis of experiments using laboratory animals. ILAR Journal, 43 CrossRef | Google Scholar | PubMed(4), 244–58.
Festing, M. F. W., Diamanti, P. and Turton, J. A. (2001). Strain differences in haematological response to chloroamphenicol succinate in mice: implications for toxicological research. Food and Chemical Toxicology, 39 CrossRef | Google Scholar(4), 375–83.
Festing, M. F. W., Overend, P., Gaines Das, R., Cortina-Borja, M. and Berdoy, M. (2002). The Design of Animal Experiments: Reducing the Use of Animals in Research through Better Experimental Design. Royal Society of Medicine Press: London Google Scholar.
Field, A. (1998). A bluffer’s guide to… sphericity. The British Psychological Society: Mathematical, Statistical & Computing Section Newsletter, 6 Google Scholar, 13–22.
Findlay, J. W. A. and Dillard, R. F. (2007). Appropriate calibration curve fitting in ligand binding assays. The AAPS Journal, 9 CrossRef | Google Scholar | PubMed(2), E260–7.
Ford, D. J. (1977). Effect of autoclaving and physical structure of diets on their utilization by mice. Laboratory Animals, 11 CrossRef | Google Scholar | PubMed(4), 235–9.
Gaines Das, R. (2004). ‘Statistics’ is not a sausage machine: a statistician’s viewpoint and some comments on experimental design. ATLA. Alternatives to Laboratory Animals, 32 Google Scholar(2), 5–8.
Gaines Das, R., Fry, D., Preziosi, R. and Hudson, M. (2009). Planning for reduction. ATLA. Alternatives to Laboratory Animals, 37 Google Scholar | PubMed(1), 27–32.
Giesbrecht, F. G. and Gumpertz, M. L. (2004). Planning, Construction, and Statistical Analysis of Comparative Experiments. Wiley & Sons, Inc. CrossRef | Google Scholar: Hoboken, NJ.
Godolphin, J. D. (2004). Simple pilot procedures for the avoidance of disconnected experimental designs. Journal of the Royal Statistical Society Series C (Applied Statistics), 53 CrossRef | Google Scholar(1), 133–47.
Gore, K. H. and Stanley, P. J. (2005). An illustration that statistical design mitigates environmental variation and ensures unambiguous study conclusions. Animal Welfare, 14 Google Scholar(4), 361–5.
Grayson, B., Idris, N. F. and Neill, J. C. (2007). Atypical antipsychotics attenuate a sub-chronic PCP-induced cognitive deficit in the novel object recognition task in the rat. Behavioural Brain Research, 184 CrossRef | Google Scholar | PubMed(1), 31–8.
Green, C. R., Ham, K. N. and Tange, J. D. (1969). Kidney lesions induced in rats by p-aminophenol. British Medical Journal, 18 CrossRef | Google Scholar(1), 162–4.
Harris, R. B. S., Zhou, J., Youngblood, B. D., et al. (1998). Effect of repeated stress on body weight and body composition of rats fed low- and high-fat diets. American Journal of Physiology – Regulatory, Integrative and Comparative Physiology, 275 CrossRef | Google Scholar | PubMed(6), R1928–38.
Hatcher, P. D., Brown, V. J., Tait, D. S., et al. (2005). 5-HT6 receptor antagonists improve performance in an attentional set shifting task in rats. Psychopharmacology, 181 CrossRef | Google Scholar(2), 253–9.
Hedenqvist, P., Roughan, J. V., Antunes, L., Orr, H. and Flecknell, P. A. (2001). Induction of anaesthesia with desflurane and isoflurane in the rabbit. Laboratory Animals, 35 CrossRef | Google Scholar | PubMed(2), 172–9.
Hille, C., Bate, S., Davis, J. and Gonzalez, M. I. (2008). 5-HT4 receptor agonism in the five-choice serial reaction time task. Behavioural Brain Research, 195 CrossRef | Google Scholar | PubMed(1), 180–6.
Hochberg, Y. (1988). A sharper Bonferroni procedure for multiple tests of significance. Biometrika, 75 CrossRef | Google Scholar(4), 800–3.
Hoenig, J. M. and Heisey, D. M. (2001). The abuse of power: the pervasive fallacy of power calculations for data analysis. The American Statistician, 55 CrossRef | Google Scholar(1), 19–24.
Holland, B. S. and Copenhaver, M. D. (1988). Improved Bonferroni-type multiple testing procedures. Psychological Bulletin, 104 CrossRef | Google Scholar(1), 145–9.
Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6 Google Scholar, 65–70.
Holson, R. R., Freshwater, L., Maurissen, J. P. J., Moser, V. C. and Phang, W. (2008). Statistical issues and techniques appropriate for developmental neurotoxicity testing: a report from the ILSI Research Foundation/Risk Science Institute expert working group on neurodevelopmental endpoints. Neurotoxicology and Teratology, 30 CrossRef | Google Scholar(4), 326–48.
Hommel, G. (1988). A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika, 75 CrossRef | Google Scholar(2), 383–6.
Hsu, J. (1996). Multiple Comparisons: Theory and Methods. Chapman and Hall/CRC: London CrossRef | Google Scholar.
Hulshoff, J. E. G, Van Dijk, K., van der Waerden, J. P. C. M., et al. (1996). Evaluation of plasma-spray and magnetron-sputter Ca-P-coated implants: an in vivo experiment using rabbits. Journal of Biomedical Materials Research, 31 CrossRef | Google Scholar(3), 329–37.
Ingram-Ross, J. L., Curran, A. K., Miyamoto, M., et al. (2012). Cardiorespiratory safety evaluation in non-human primates. Journal of Pharmacological and Toxicological Methods, 66 CrossRef | Google Scholar | PubMed, 114–24.
Jones, B. and Kenward, M. G. (2003). Design and Analysis of Cross-Over Trials. Chapman and Hall/CRC: London Google Scholar.
Kalinichev, M., Bate, S. T. and Jones, D. N. C. (2009). Models of aspects of schizophrenia: behavioral sensitization induced by subchronic phencyclidine administration. Current Protocols in Pharmacology, 45 Google Scholar, 5.54.1–13.
Karp, N. A., Segonds-Pichon, A., Gerdin, A. K. B., Ramirez-Solis, R. and White, J. K. (2012). The fallacy of ratio correction to address confounding factors. Laboratory Animals, 46 CrossRef | Google Scholar | PubMed(3), 245–52.
Keuls, M. (1952). The use of the ‘studentized range’ in connection with an analysis of variance. Euphytica, 1 CrossRef | Google Scholar(2), 112–22.
Kilkenny, C., Brown, W. J., Cuthill, I. C., Emerson, M. and Altman, D. G. (2010). Improving bioscience research: the ARRIVE guidelines for reporting animal research. PLoS Biol, 8 CrossRef | Google Scholar | PubMed(6), e1000412.
Kilkenny, C., Parsons, N., Kadyszewski, E., et al. (2009). Survey of the quality of experimental design, statistical analysis and reporting of research using animals. PLoS One, 4 CrossRef | Google Scholar | PubMed(11), e7824.
Kleinbaum, D. G. and Klein, M. (2005). Survival Analysis: A Self-Learning Text, 2nd edition. Springer: New York Google Scholar.
Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell’Istituto Italiano degli Attuari, 4 Google Scholar(1), 83–91.
Kramer, C. Y. (1956). Extension of multiple range tests to group means with unequal numbers of replications. Biometrics, 12 CrossRef | Google Scholar(3), 307–10.
Kuentz, M., Rothlisberger, D. and Richter, W. (2003). Design of experiment (DoE) methods maximize information from a minimal number of animals in special cases of preclinical bioavailability testing. Pharmaceutical Development and Technology, 8 CrossRef | Google Scholar | PubMed(4), 453–8.
Kwan, K. Y., Allchome, A. J., Vollrath, M. A., et al. (2006). TRPA1 contributes to cold, mechanical, and chemical nociception but is not essential for hair-cell transduction. Neuron, 50 CrossRef | Google Scholar, 277–89.
Lazic, S. E. (2010). The problem of pseudoreplication in neuroscientific studies: is it affecting your analysis?BMC Neuroscience, 11 CrossRef | Google Scholar | PubMed(1), 5.
Lehmann, E. L. (1999). Elements of Large-Sample Theory. Springer CrossRef | Google Scholar: New York.
Levene, H. (1960). Robust tests for equality of variances. In Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling, editors Olkin, I., Ghurye, S. G., Hoeffding, W., Madow, W. G. and Mann, H. B.278–292. Stanford University Press: Stanford, CA Google Scholar.
Liao, J. J. Z. and Liu, R. (2009). Re-parameterization of five-parameter logistic function. Journal of Chemometrics, 23 CrossRef | Google Scholar(5), 248–53.
Ludbrook, J. (1998). Multiple comparison procedures updated. Clinical and Experimental Pharmacology and Physiology, 25 CrossRef | Google Scholar | PubMed(12), 1032–7.
Macleod, M. R., Fisher, M., O’Collins, V., et al. (2009). Reprint: good laboratory practice: preventing introduction of bias at the bench. Journal of Cerebral Blood Flow and Metabolism, 29 CrossRef | Google Scholar | PubMed, 2213.
Maheswaran, S., Barjat, H., Rueckert, D., et al. (2009). Longitudinal regional brain volume changes quantified in normal aging and Alzheimer’s APP × PS1 mice using MRI. Brain Research, 1270 CrossRef | Google Scholar | PubMed, 19–32.
Manser, C. E., Broom, D. M., Overend, P. and Morris, T. H. (1998). Investigations into the preferences of laboratory rats for nest-boxes and nesting materials. Laboratory Animals, 32 CrossRef | Google Scholar | PubMed(1), 23–35.
Mathew, G., Watson, D. I., Rofe, A. M., et al. (1996). Wound metastases following laparoscopic and open surgery for abdominal cancer in a rat model. British Journal of Surgery, 83 CrossRef | Google Scholar(8), 1087–90.
Mauchly, J. W. (1940). Test for sphericity of a normal n-variate distribution. Annals of Mathematical Statistics, 11 CrossRef | Google Scholar(2), 204–9.
McCance, I. (1995). Assessment of statistical procedures used in papers in the Australian Veterinary Journal. Australian Veterinary Journal, 72 CrossRef | Google Scholar | PubMed(9), 322–8.
McQuade, R., Creton, D. and Stanford, S. C. (1999). Effect of novel environmental stimuli on rat behaviour and central noradrenaline function measured by in vivo microdialysis. Psychopharmacology, 145 CrossRef | Google Scholar | PubMed(4), 393–400.
Mead, R. (1988). The Design of Experiments: Statistical Principles for Practical Applications. Cambridge University Press: Cambridge Google Scholar.
Mead, R., Curnow, R. N. and Hasted, A. M. (2003). Statistical Methods in Agriculture and Experimental Biology, 3rd edition. Chapman and Hall/CRC: London Google Scholar.
Miller, R. G. (1981). Simultaneous Statistical Inference, 2nd edition. Springer-Verlag CrossRef | Google Scholar: New York.
Milliken, G. A. and Johnson, D. E. (2002). Analysis of Messy Data Volume III: Analysis of Covariance. Chapman & Hall/CRC: New York Google Scholar.
Miyazaki, H., Watanabe, H., Kitayama, T., et al. (2005). QT PRODACT: sensitivity and specificity of the canine telemetry assay for detecting drug-induced QT interval prolongation. Journal of Pharmacological Sciences, 99 CrossRef | Google Scholar | PubMed, 523–9.
Montgomery, D. C. (1997). Design and Analysis of Experiments, 4th edition. Wiley Google Scholar: New York.
Morris, T. R. (1999). Experimental Design and Analysis in Animal Sciences. CABI Publishing: Wallingford, UK Google Scholar.
Murphy, N., Bruckdorfer, K. R., Grimsditch, D. C., et al. (2003). Temporal relationships between circulating levels of CC and CXC chemokines and developing atherosclerosis in Apolipoprotein E*3 Leiden mice. Arteriosclerosis, Thrombosis, and Vascular Biology, 23 CrossRef | Google Scholar | PubMed, 1615–20.
Nakagawa, S. (2004). A farewell to Bonferroni: the problems of low statistical power and publication bias. Behavioral Ecology, 15 CrossRef | Google Scholar(6), 1044–5.
Nesnow, S., Mass, M. J., Ross, J. A., et al. (1998). Lung tumourigenic interactions in strain A/J mice of five environmental polycyclic aromatic hydrocarbons. Environmental Health Perspectives, 106 CrossRef | Google Scholar(Suppl 6), 1337–46.
Newman, D. (1939). The distribution of range in samples from a normal population, expressed in terms of an independent estimate of standard deviation. Biometrika, 31 CrossRef | Google Scholar(1/2), 20–30.
Nieuwenhuis, S., Forstmann, B. U. and Wagenmakers, E. J. (2011). Erroneous analyses of interactions in neuroscience: a problem of significance. Nature Neuroscience, 14 CrossRef | Google Scholar | PubMed(9), 1105–7.
Onyango, E. M. and Adeola, O. (2011). Dietary cholecalciferol lowers the maximal activity of intestinal mucosa phytase in ducklings fed low-phosphorus diets. Canadian Journal of Animal Science, 91 CrossRef | Google Scholar(3), 399–404.
Parkin, S. L., Pritchett, J. P., Grimsditch, D. C., et al. (2004). Circulating levels of the chemokines JE and KC in female C3H apolipoprotein-E-deficient and C57BL apolipoprotein-E-deficient mice as potential markers of atherosclerosis development. Biochemical Society Transactions, 32 CrossRef | Google Scholar | PubMed(1), 128–30.
Patel, S. R., Murphy, K. G., Thompson, E. L., et al. (2008). Pyroglutamylated RFamide peptide 43 stimulates the hypothalamic-pituitary-gonadal axis via gonadotropin-releasing hormone in rats. Endocrinology, 149 CrossRef | Google Scholar | PubMed(9), 4747–54.
Pinheiro, J., Bates, D., DebRoy, S. and Sarkar, D. (2008 Google Scholar). The R Development Core Team. nlme: linear and nonlinear mixed effects models. R package version 3.1–93. R Foundation for Statistical Computing, Vienna, Austria. .
Plackett, R. L. and Burman, J. P. (1946). The design of optimal multifactorial experiments. Biometrika, 33 CrossRef | Google Scholar(4), 305–25.
Pugh, P. L., Richardson, J. C., Bate, S. T., Upton, N. and Sunter, D. (2007). Non-cognitive behaviours in an APP/PS1 transgenic model of Alzheimer’s disease. Behavioural Brain Research, 178 CrossRef | Google Scholar(1), 18–28.
R Development Core Team (2012). R: A language and environment for statistical computing Google Scholar. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3–900051–07–0, .
Rooke, E. D. M., Vesterinen, H. M., Sena, E. S., Egan, K. J. and Macleod, M. R. (2011). Dopamine agonists in animal models of Parkinson’s disease: A systematic review and meta-analysis. Parkinsonism and Related Disorders, 17 CrossRef | Google Scholar | PubMed(5), 313–20.
Rosnow, R. L. and Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist, 44 CrossRef | Google Scholar(10), 1276–84.
Rumble, R., Saville, M., Simmons, L., et al. (2005). The preference of the common marmoset for nest boxes made from three different materials – wood, plastic, metal. Animal Technology and Welfare, 4 Google Scholar(3), 185–7.
Russell, W. M. S. and Burch, R. L. (1959). The Principles of Humane Experimental Technique. Methuen & Co. Ltd: London Google Scholar.
Ruxton, G. G. and Colegrave, N. (2006). Experimental Design for the Life Sciences. OxfordUniversity Press: Oxford Google Scholar.
Scheffé, H. (1953). A method for judging all contrasts in the analysis of variance. Biometrika, 40 Google Scholar(1–2), 87–110.
Schleiss, M. R., Anderson, J. L. and McGregor, A. (2006). Cyclic cidofovir (cHPMPC) prevents congenital cytomegalovirus infection in a guinea pig model. Virology Journal, 3 CrossRef | Google Scholar, 9.
Seacat, A. M., Thomford, P. J., Hansen, K. J., et al. (2002). Subchronic toxicity studies on perfluorooctanesulfonate potassium salt in cynomolgus monkeys. Toxicological Sciences, 68 CrossRef | Google Scholar | PubMed(1), 249–64.
Semela, D., Piguet, A. C., Kolev, M., et al. (2007). Vascular remodeling and antitumoral effects of mTOR inhibition in a rat model of hepatocellular carcinoma. Journal of Hepatology, 46 CrossRef | Google Scholar(5), 840–8.
Sena, E. S., van der Worp, H. B., Bath, P. M. W., Howells, D. W. and Macleod, M. R. (2010). Publication bias in reports of animal stroke studies leads to major overstatement of efficacy. PLoS Biol, 8 CrossRef | Google Scholar(3), e1000344.
Shaffer, J. P. (1995). Multiple hypothesis testing. Annual Review of Psychology, 46 CrossRef | Google Scholar, 561–84.
Shapiro, S. S. and Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52 CrossRef | Google Scholar(3–4), 591–9.
Shaw, R. (2004). Reduction in laboratory animal use by factorial design. Alternatives to Laboratory Animals: ATLA, 32 Google Scholar | PubMed(2), 49–51.
Shaw, R., Festing, M. F. W., Peers, I. and Furlong, L. (2002). Use of factorial designs to optimize animal experiments and reduce animal use. ILAR Journal, 43 CrossRef | Google Scholar | PubMed(4), 223–32.
Shoaib, M., Sidhpura, N. and Shafait, S. (2003). Investigating the actions of bupropion on dependence-related effects of nicotine in rats. Psychopharmacology 165 CrossRef | Google Scholar | PubMed, 404–12.
Shirley, E. A. C. (1977). The analysis of organ weight data. Toxicology, 8 CrossRef | Google Scholar | PubMed, 13–22.
Šidák, Z. (1967). Rectangular confidence regions for the means of multivariate normal distributions. Journal of the American Statistical Association, 62 Google Scholar(318), 626–33.
Singleton, K. D. and Wischmeyer, P. E. (2003). Distance of cecum ligated influences mortality, tumor necrosis factor-alpha and interleukin-6 expression following cecal ligation and puncture in the rat. European Surgical Research, 35 CrossRef | Google Scholar | PubMed(6), 486–91.
Sjödin, L., Visser, S. and Al-Saffar, A. (2011). Using pharmacokinetic modeling to determine the effect of drug and food on gastrointestinal transit in dogs. Journal of Pharmacological and Toxicological Methods, 64 CrossRef | Google Scholar | PubMed(1), 42–52.
Skene, S. S. and Kenward, M. G. (2010). The analysis of very small samples of repeated measurements I: an adjusted sandwich estimator. Statistics in Medicine, 29 CrossRef | Google Scholar | PubMed(27), 2825–37.
Slob, W. (2002). Dose-response modeling of continuous endpoints. Toxicological Sciences, 66 CrossRef | Google Scholar | PubMed(2), 298–312.
Slotten, H. A., Kalinichev, M., Hagan, J. J., Marsden, C. A. and Fone, K. C. F. (2006). Long-lasting changes in behavioural and neuroendocrine indices in the rat following neonatal maternal separation: gender-dependent effects. Brain Research, 1097 CrossRef | Google Scholar | PubMed(1), 123–32.
Smirnov, N. V. (1939). Estimation of deviation between empirical distribution functions in two independent samples. Bulletin Moscow University, 2 Google Scholar(2), 3–16.
Smith, P. F. (2012). A note on the advantages of using linear mixed model analysis with maximal likelihood estimation over repeated measures ANOVAs in psychopharmacology: comment on Clark et al. (2012). Journal of Psychopharmacology, 26 CrossRef | Google Scholar(12), 1605–7.
Smith, C. C., Adkins, D. J., Martin, E. A. and O’Donovan, M. R. (2008). Recommendations for design of the rat comet assay. Mutagenesis, 23 CrossRef | Google Scholar | PubMed(3), 233–40.
Snedecor, G. W. and Cochran, W. G. (1989). Statistical Methods, 8th edition. Iowa State University Press: Ames, IA Google Scholar.
Stufken, J. (1996). Optimal crossover designs. In Handbook of Statistics 13: Design and Analysis of Experiments, editors Ghosh, S. and Rao, C. R.63–90. North-Holland Google Scholar: Amsterdam.
Tallarida, R. J. (2000). Drug Synergism and Dose-Effect Data Analysis. Chapman and Hall/CRC Press: Boca Raton, FL CrossRef | Google Scholar.
Tallarida, R. J. and Jacob, L. S. (1979). The Dose-Response Relation in Pharmacology. Springer-Verlag CrossRef | Google Scholar: New York.
Teng, Y. D., Lavik, E. B., Qu, X., et al. (2002). Functional recovery following traumatic spinal cord injury mediated by a unique polymer scaffold seeded with neural stem cells. Proceedings of the National Academy of Sciences, 99 CrossRef | Google Scholar | PubMed(5), 3024–9.
Toothaker, L. E. (1993). Multiple Comparison Procedures. No. 89. SAGE Publications Inc.: London, UK CrossRef | Google Scholar.
Torrallardona, D., Conde, M. R., Badiola, I., Polo, J. and Brufau, J. (2003). Effect of fishmeal replacement with spray-dried animal plasma and colistin on intestinal structure, intestinal microbiology, and performance of weanling pigs challenged with Escherichia coli K99. Journal of Animal Science, 81 CrossRef | Google Scholar | PubMed(5), 1220–6.
Tufte, E. R. (1983). The Visual Display of Quantitative Information. Graphics Press Google Scholar: Cheshire, CT.
Tukey, J. W. (1953). The Problem of Multiple Comparisons Google Scholar. Unpublished Notes, Princeton University.
van der Worp, H. B., Howells, D. W., Sena, E. S., et al. (2010). Can animal models of disease reliably inform human studies?PLoS Medicine, 7 CrossRef | Google Scholar | PubMed(3), e1000245.
Vesterinen, H. M., Sena, E. S., ffrench-Constant, C., et al. (2010). Improving the translational hit of experimental treatments in multiple sclerosis. Multiple Sclerosis, 16 CrossRef | Google Scholar | PubMed(9), 1044–55.
Wiklund, S. J. and Agurell, E. (2003). Aspects of design and statistical analysis in the Comet assay. Mutagenesis, 18 CrossRef | Google Scholar | PubMed(2), 167–75.
Williams, E. J. (1949). Experimental designs balanced for the estimation of residual effects of treatments. Australian Journal of Scientific Research Series A, 2 Google Scholar, 149–68.
Wolfram, S., Raederstorff, D., Preller, M., et al. (2006). Epigallocatechin gallate supplementation alleviates diabetes in rodents. The Journal of Nutrition, 136 CrossRef | Google Scholar | PubMed, 2512–18.
Woolley, M. L., Pemberton, D. J., Bate, S., Corti, C. and Jones, D. N. C. (2008). The mGlu2 but not the mGlu3 receptor mediates the actions of the mGluR2/3 agonist, LY379268, in mouse models predictive of antipsychotic activity. Psychopharmacology, 196 CrossRef | Google Scholar(3), 431–40.

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