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Experimental Design and Data Analysis for Biologists
Abstract
An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and links to software.
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“VIFs did not reveal collinearity problems, as indicated by the largest value being <4 (51) (event model 2.59; anticipation model 2.43; defection model 1.98; intergroup conflict type model 2.74; persistence model 2.03; reduced event model 2.72).”
From Oxytocin reactivity during intergroup conflict in wild chimpanzees (2017) · cites this paper as [51]
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Elevation alters ecosystem properties across temperate treelines globally
Mayor, J. R., Sanders, N. J., Classen, A. T., Bardgett, R. D., Clément, J.-C., Fajardo, A., Lavorel, S., Sundqvist, M. K., Bahn, M., Chisholm, C., et al. (2017) · Nature · doi:10.1038/nature21027 · Cited by 325
Deterministic Plio‐Pleistocene extinctions in the European cool‐temperate tree flora
Svenning, J. (2003) · Ecology Letters · doi:10.1046/j.1461-0248.2003.00477.x · Cited by 320
“*Using the 90% criterion (Quinn & Keough 2002) only the first two components were used for further analyses.”
Estimation of parameters in complex 15N tracing models by Monte Carlo sampling
Müller, C., Rütting, T., Kattge, J., Laughlin, R. J., & Stevens, R. J. (2006) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2006.09.021 · Cited by 319
“8 indicate pairs or groups of parameters that tend to be strongly constrained together (Quinn and Keough, 2002).”
BackgroundNoise pollution is pervasive in U.S. protected areas
Buxton, R. T., McKenna, M. F., Mennitt, D. J., Fristrup, K. M., Crooks, K. R., Angeloni, L. M., & Wittemyer, G. (2017) · Science · doi:10.1126/science.aah4783 · Cited by 325
DMSP biosynthesis by an animal and its role in coral thermal stress response
Raina, J., Tapiolas, D. M., Forêt, S., Lutz, A., Abrego, D., Ceh, J., Seneca, F., Clode, P. L., Bourne, D. G., Willis, B. L., et al. (2013) · Nature · doi:10.1038/nature12677 · Cited by 320
Individual and combined responses of stream ecosystems to multiple stressors
Townsend, C. R., Uhlmann, S. S., & Matthaei, C. D. (2008) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2008.01548.x · Cited by 311
Are Pinus halepensis plantations useful as a restoration tool in semiarid Mediterranean areas?
Maestre, F. T., & Cortina, J. (2004) · Forest Ecology and Management · doi:10.1016/j.foreco.2004.05.040 · Cited by 311
“These are excellent explorative tools, but may lead to erroneous conclusions for several reasons, including the presence of hidden factors and spurious relationships (Quinn and Keough, 2002).”
BackgroundAssessment of ecological status in U.K. rivers using diatoms
KELLY, M. G., Juggins, S., GUTHRIE, R., et al. (2007) · Freshwater Biology · doi:10.1111/j.1365-2427.2007.01903.x · Cited by 309
Paul, N. A., de Nys, R., & Steinberg, P. D. (2006) · Marine Ecology Progress Series · doi:10.3354/meps306087 · Cited by 309
“Where appropriate, transformations of the data (detailed in ‘Results’) were made to satisfy the ANOVA assumptions of normality and heterogeneity of variance (Quinn & Keough 2002).”
MethodSmith, P. F., Ganesh, S., & Liu, P. (2013) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2013.08.024 · Cited by 305
Ice age legacies in the geographical distribution of tree species richness in Europe
Svenning, J., & Skov, F. (2006) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2006.00280.x · Cited by 304
“Multicollinearity is likely to be a problem when variables are highly correlated, with r ≥ 0.90 and tolerance < 0.10 (Tabachnick & Fidell, 2001; Quinn & Keough, 2002).”
BackgroundInfluentialDynamic factor analysis to estimate common trends in fisheries time series
Zuur, A. F., Tuck, I. D., & Bailey, N. (2003) · Canadian Journal of Fisheries and Aquatic Sciences · doi:10.1139/f03-030 · Cited by 306
“Heteroscedasticity of residuals can also be dealt with by data transformations (Quinn and Keough 2002).”
BackgroundDeslauriers, A., Rossi, S., Anfodillo, T., & Saracino, A. (2008) · Tree Physiology · doi:10.1093/treephys/28.6.863 · Cited by 302
“The logistic regression takes the general form: 12 j x x x xLogit 10) 1 ln()( (Eqn 1) 13 where x is the probability of xylogenesis being active, xj is the temperature on a given day j, 0 14 and 1 are intercept and slope of the logit regression (Quinn and Keough 2002).”
BackgroundMethodInfluentialFinal Collapse of the Neyman-Pearson Decision Theoretic Framework and Rise of the neoFisherian
Hurlbert, S. H., & Lombardi, C. M. (2009) · Annales Zoologici Fennici · doi:10.5735/086.046.0501 · Cited by 305
“As Quinn and Keough (2002) nicely state, in the great majority of situations, a " rejection of the H 0 is not important because we thought the H 0 might be true.”
BackgroundDispersal of adult aquatic insects in catchments of differing land use
Petersen, I., Masters, Z., Hildrew, A., & Ormerod, S. (2004) · Journal of Applied Ecology · doi:10.1111/j.0021-8901.2004.00942.x · Cited by 308
“This procedure provides more power for the individual tests and is recommended in favour of the conventional Bonferroni procedure (Quinn & Keough 2002).”
Fern species richness along a central Himalayan elevational gradient, Nepal
Bhattarai, K. R., Vetaas, O. R., & Grytnes, J. (2004) · Journal of Biogeography · doi:10.1046/j.0305-0270.2003.01013.x · Cited by 297
“Q diagnostic plot (Crawley, 1993, 2002; Hastie & Pregibon, 1993; Quinn & Keough, 2002).”
Resource dilution effects on specialist insect herbivores in a grassland biodiversity experiment
Otway, S. J., Hector, A., & Lawton, J. H. (2005) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2005.00913.x · Cited by 291
García‐Palacios, P., McKie, B. G., Handa, I. T., Frainer, A., & Hättenschwiler, S. (2015) · Functional Ecology · doi:10.1111/1365-2435.12589 · Cited by 294
Microbial richness and composition independently drive soil multifunctionality
Delgado‐Baquerizo, M., Trivedi, P., Trivedi, C., Eldridge, D. J., Reich, P. B., Jeffries, T. C., & Singh, B. K. (2017) · Functional Ecology · doi:10.1111/1365-2435.12924 · Cited by 299
“For the Microcosm study (replicated approach), we examined the effects of diversity on multifunctionality by conducting a nested ANOVA, with diversity as a fixed factor and bacterial combination (Table S1) as a random factor nested within diversity (Quinn & Keough, 2002).”
MethodAmphibian species richness across environmental gradients
Werner, E. E., Skelly, D. K., Relyea, R. A., & Yurewicz, K. L. (2007) · Oikos · doi:10.1111/j.0030-1299.2007.15935.x · Cited by 310
“In order to identify important potential causal variables having independent effects on species richness we employed hierarchical partitioning (Mac Nally 2002, Quinn and Keough 2006).”
MethodDeep cold‐water corals as nurseries for fish larvae
Baillon, S., Hamel, J., Wareham, V. E., & Mercier, A. (2012) · Frontiers in Ecology and the Environment · doi:10.1890/120022 · Cited by 302
Martin, D., Sale, C., Cooper, S. B., & Elliott-Sale, K. J. (2017) · International Journal of Sports Physiology and Performance · doi:10.1123/ijspp.2017-0330 · Cited by 292
Healy, S., Nacario, A., Braithwaite, R. E., & Hopper, C. A. (2018) · Autism Research · doi:10.1002/aur.1955 · Cited by 327
“…interventions INSAR researchers to make a clear and sensible interpretation of whichever variables they are attempting to detect within their research, whereas quasi-experimental designs are subject to internal validity as participants may not be comparable at baseline (Quinn & Keough, 2002).”
BackgroundSpatial–temporal patterns in Mediterranean carnivore road casualties: Consequences for mitigation
Grilo, C., Bissonette, J. A., & Santos‐Reis, M. (2008) · Biological Conservation · doi:10.1016/j.biocon.2008.10.026 · Cited by 290
“Exact binomial tests were used to determine if there were significant differences in the occurred number of accidents among biological periods (Quinn and Keough, 2002).”
MethodNear-future levels of ocean acidification reduce fertilization success in a sea urchin
Havenhand, J. N., Buttler, F., Thorndyke, M. C., & Williamson, J. E. (2008) · Current Biology · doi:10.1016/j.cub.2008.06.015 · Cited by 287
Changes in biocrust cover drive carbon cycle responses to climate change in drylands
Maestre, F. T., Escolar, C., de Guevara, M. L., Quero, J. L., Lázaro, R., Delgado‐Baquerizo, M., Ochoa, V., Berdugo, M., Gozalo, B., & Gallardo, A. (2013) · Global Change Biology · doi:10.1111/gcb.12306 · Cited by 290
“Because of the low CO2 efflux rates typically observed in areas such as those studied here (Castillo-Monroy et al., 2011; Rey et al., 2011), each measurement period was 120 s to ensure reliable measurements.”
BackgroundMethodPyšek, P., Jaros̆ı́k, V., Pergl, J., Randall, R. P., Chytrý, M., Kühn, I., Tichý, L., Danihelka, J., Chrtek, J., & Sádlo, J. (2009) · Diversity and Distributions · doi:10.1111/j.1472-4642.2009.00602.x · Cited by 285
“To check appropriateness of the trees, residuals were plotted against predicted values of their terminal nodes (Quinn & Keough, 2002).”
MethodPiola, R. F., & Johnston, E. L. (2007) · Diversity and Distributions · doi:10.1111/j.1472-4642.2007.00430.x · Cited by 285
Global biogeography and ecology of body size in birds
Olson, V., Davies, R. G., Orme, C. D. L., Thomas, G. H., Meiri, S., Blackburn, T. M., Gaston, K. J., Owens, I. P. F., & Bennett, P. M. (2009) · Ecology Letters · doi:10.1111/j.1461-0248.2009.01281.x · Cited by 285
Allen, R. M., Buckley, Y. M., & Marshall, D. J. (2007) · The American Naturalist · doi:10.1086/524952 · Cited by 291
Ascoli, D., Vacchiano, G., Turco, M., Conedera, M., Drobyshev, I., Maringer, J., Motta, R., & Hacket‐Pain, A. J. (2017) · Nature Communications · doi:10.1038/s41467-017-02348-9 · Cited by 286
Zou, J., Huang, Y., Zheng, X., & Wang, Y. (2007) · Atmospheric Environment · doi:10.1016/j.atmosenv.2007.06.049 · Cited by 282
“The OLS point estimates require no distributional assumptions for variables, but instead concentrate on residual distribution (Quinn and Keough, 2004).”
BackgroundMethodInfluentialGene flow maintains a large genetic difference in clutch size at a small spatial scale
Postma, E., & van Noordwijk, A. J. (2005) · Nature · doi:10.1038/nature03083 · Cited by 281
Global effects of non‐native tree species on multiple ecosystem services
Castro‐Díez, P., Vaz, A. S., Silva, J. S., van Loo, M., Alonso, Á., Aponte, C., Bayón, Á., Bellingham, P. J., Chiuffo, M. C., DiManno, N., et al. (2019) · Biological Reviews · doi:10.1111/brv.12511 · Cited by 281
Particulate matter deposition on roadside plants and the importance of leaf trait combinations
Leonard, R. J., McArthur, C., & Hochuli, D. F. (2016) · Urban forestry & urban greening · doi:10.1016/j.ufug.2016.09.008 · Cited by 280
de Oliveira‐Filho, A. T., Budke, J. C., Jarenkow, J. A., Eisenlohr, P. V., & Neves, D. M. (2013) · Journal of Plant Ecology · doi:10.1093/jpe/rtt058 · Cited by 275
“We then performed an additional and progressive elimination of collinear variables based on their Variance Inflation Factor (VIF) until maintaining only those with VIF < 10 (Quinn and Keough 2002).”
MethodTaxonomic bias in reintroduction projects
Seddon, P. J., Soorae, P. S., & Launay, F. J. P. (2005) · Animal Conservation · doi:10.1017/s1367943004001799 · Cited by 275
“These standardised residuals, also called Pearson residuals, are directly comparable irrespective of absolute frequencies (Quinn & Keough, 2002).”
BackgroundLeighton, P. A., Koffi, J. K., Pelcat, Y., Lindsay, L. R., & Ogden, N. H. (2012) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2012.02112.x · Cited by 273
“All continuous predictors were standardized (mean = 0, SD = 1) to allow meaningful comparison of coefficients (Quinn & Keough 2002).”
MethodMortelliti, A., Amori, G., & Boitani, L. (2010) · Oecologia · doi:10.1007/s00442-010-1623-3 · Cited by 274
“However, carefully following (or approximating) an appropriate factorial design (Quinn and Keough 2002) will surely”
BackgroundTopography, energy and the global distribution of bird species richness
Davies, R. G., Orme, C. D. L., Štorch, D., Olson, V., Thomas, G. H., Ross, S. G., Ding, T., Rasmussen, P. C., Bennett, P. M., Owens, I. P. F., et al. (2007) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2006.0061 · Cited by 270
“We tested for collinearity among predictors through investigations of tolerance levels (Quinn & Keough 2002).”
MethodInteracting effects of farming practice and landscape context on bumble bees
Rundlöf, M., Nilsson, H. J., & Smith, H. G. (2008) · Biological Conservation · doi:10.1016/j.biocon.2007.10.011 · Cited by 272
Rees, G. N., Baldwin, D. S., Watson, G. O., Perryman, S. E., & Nielsen, D. L. (2004) · Antonie van Leeuwenhoek · doi:10.1007/s10482-004-0498-x · Cited by 274
“Animal and plant ecologists examining community patterns have developed and applied a range of tools to analyze community structure Lambshead 1986; Shiel 1990; Clarke 1993; – and references there in; Nielsen et al. 1997; Quinn and Keogh 2002 .”
BackgroundMethodTemporal dynamics and diversity of avian malaria parasites in a single host species
Bensch, S., Waldenström, J., Jonzén, N., et al. (2006) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2006.01176.x · Cited by 270
Systems biology: experimental design
Kreutz, C., & Timmer, J. (2009) · The FEBS Journal · doi:10.1111/j.1742-4658.2008.06843.x · Cited by 257
Inference in ecology and evolution
Stephens, P. A., Buskirk, S. W., & del Rio, C. M. (2006) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2006.12.003 · Cited by 268
Consumer diversity interacts with prey defenses to drive ecosystem function
Rasher, D. B., Hoey, A. S., & Hay, M. E. (2013) · Ecology · doi:10.1890/12-0389.1 · Cited by 269
Postglacial dispersal limitation of widespread forest plant species in nemoral Europe
Svenning, J., Normand, S., & Skov, F. (2008) · Ecography · doi:10.1111/j.0906-7590.2008.05206.x · Cited by 258
Climate-smart sustainable agriculture in low-to-intermediate shade agroforests
Blaser‐Hart, W. J., Oppong, J., Hart, S. P., Landolt, J., Yeboah, E., & Six, J. (2018) · Nature Sustainability · doi:10.1038/s41893-018-0062-8 · Cited by 282
Cumulative nitrogen input drives species loss in terrestrial ecosystems
Schrijver, A. D., Frenne, P. D., Ampoorter, E., Nevel, L. V., Demey, A., Wuyts, K., & Verheyen, K. (2011) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2011.00652.x · Cited by 263
Vonk, J. E., Tank, S. E., Mann, P. J., Spencer, R. G. M., Treat, C. C., Striegl, R. G., Abbott, B. W., & Wickland, K. P. (2015) · Biogeosciences · doi:10.5194/bg-12-6915-2015 · Cited by 259
Albrecht, M., Duelli, P., MÜLLER, C. B., Kleijn, D., & Schmid, B. (2007) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2007.01306.x · Cited by 261
Theis, K. R., Romero, R. J., Winters, A. D., Greenberg, J. M., Gomez‐Lopez, N., Alhousseini, A., Bieda, J., Maymon, E., Pacora, P., Fettweis, J. M., et al. (2019) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2018.10.018 · Cited by 264
Fabian, D. K., Kapun, M., Nolte, V., Kofler, R., SCHMIDT, P. S., Schlötterer, C., & Flatt, T. (2012) · Molecular Ecology · doi:10.1111/j.1365-294x.2012.05731.x · Cited by 248
“We did not fit the interaction term since ANOVA applied to ranktransformed data is inappropriate for interpreting interactions (Quinn & Keough 2002).”
MethodBoedeltje, G., Bakker, J. P., Bekker, R. M., et al. (2003) · Journal of Ecology · doi:10.1046/j.1365-2745.2003.00820.x · Cited by 255
“…of diversity and abundance of the diaspores trapped, frequency of occurrence was arcsine-transformed and the number of trapped diaspores, life-history data and distance to the nearest stand were log10-transformed because the residuals did not follow a normal distribution (Quinn & Keough 2002).”
BackgroundMethodNorling, K., Rosenberg, R., Hulth, S., Grémare, A., & Bonsdorff, E. (2007) · Marine Ecology Progress Series · doi:10.3354/meps332011 · Cited by 254
“…we used graphical exploratory techniques to check data for assumptions concerning normal distribution (probability plots) and homogeneity of variances (box plots) and, where appropriate, data transformations were applied to reduce effects of single outliers and skewed data (Quinn & Keough 2002).”
MethodLebrija‐Trejos, E., Bongers, F., Pérez-García, E. A., & Meave, J. A. (2008) · Biotropica · doi:10.1111/j.1744-7429.2008.00398.x · Cited by 250
“…scaling module (SPSS 2003) selecting the Simplex method as starting configuration; dimensions were fixed at two, as Kruskal’s measures of stress reached levels adequately representing actual dissimilarities between samples (0.132 and 0.152 for analyses 1 and 2, respectively; Quinn & Keough 2002).”
MethodInfluentialALLOMETRIC EXPONENTS DO NOT SUPPORT A UNIVERSAL METABOLIC ALLOMETRY
White, C. R., Cassey, P., & Blackburn, T. M. (2007) · Ecology · doi:10.1890/05-1883 · Cited by 252
Food plant diversity as broad-scale determinant of avian frugivore richness
Kissling, W. D., Rahbek, C., & Böhning‐Gaese, K. (2007) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2006.0311 · Cited by 248
“These transformations yielded the best approximations of normal distributions and were performed to meet the normality of errors assumption (Mitchell 1992; Quinn & Keough 2002).”
BackgroundMethodInfluentialWild Chimpanzees Exchange Meat for Sex on a Long-Term Basis
Gomes, C. M., & Boesch, C. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005116 · Cited by 249
“General results were presented using the trimmed mean which is sensitive to skewed data [37], the first quartile (Q1) and third quartile (Q3) throughout.”
MethodConditional outcomes in plant–herbivore interactions: neighbours matter
Baraza, E., Zamora, R., & Hódar, J. A. (2006) · Oikos · doi:10.1111/j.0030-1299.2006.14265.x · Cited by 249
“This variable was analysed by using loglinear models (Quinn and Keough 2002), taking mountain range, plot nested in mountain range, sapling species, and experimental microhabitat as factors, while the state of the sapling at the beginning and at the end of summer drought were taken as response variables.”
MethodInfluentialAsch, R. G. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1421946112 · Cited by 262
“Because several ecological characteristics of fishes were correlated, PCA was used to identify major modes of variability among the ecological characteristics.”
MethodInfluentialFood habits of the world's grey wolves
Newsome, T. M., Boitani, L., Chapron, G., Ciucci, P., Dickman, C. R., Dellinger, J. A., López‐Bao, J. V., Peterson, R. O., Shores, C. R., Wirsing, A. J., et al. (2016) · Mammal Review · doi:10.1111/mam.12067 · Cited by 256
“We chose non- metric multidimensional scaling because it provides a graphical representation of the results, while ANOSIM provides a measure of dissimilarity (R) among and within selected groupings (Quinn & Keough 2002).”
MethodMalo, A. F., Garde, J. J., Soler, A. J., et al. (2004) · Biology of Reproduction · doi:10.1095/biolreprod.104.036368 · Cited by 246
“We performed a principal component analysis (PCA) to explore relationships between variables and to assess how much of the overall variance is shared by the different sperm traits [41].”
MethodBeaulieu, M., Pick, F. R., & Gregory‐Eaves, I. (2013) · Limnology and Oceanography · doi:10.4319/lo.2013.58.5.1736 · Cited by 243
Coping with environmental uncertainty: dynamic bet hedging as a maternal effect
Crean, A. J., & Marshall, D. J. (2009) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2008.0237 · Cited by 238
Early Social Networks Predict Survival in Wild Bottlenose Dolphins
Stanton, M. A., & Mann, J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0047508 · Cited by 237
“Because network metrics are often correlated, multicollinearity among explanatory variables was assessed using variance inflation factors (VIFs), with VIFs greater than 10 typically considered indicative of severe collinearity [39].”
MethodBecker, A., Whitfield, A. K., Cowley, P. D., Järnegren, J., & Næsje, T. F. (2012) · Journal of Applied Ecology · doi:10.1111/1365-2664.12024 · Cited by 235
Model‐based approaches to unconstrained ordination
Hui, F. K. C., Taskinen, S., Pledger, S., Foster, S. D., & Warton, D. I. (2014) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12236 · Cited by 234
Finney, J. C., Pettay, D. T., Sampayo, E. M., et al. (2010) · Microbial Ecology · doi:10.1007/s00248-010-9681-y · Cited by 237
A Survey on Multidimensional Scaling
Saeed, N., Nam, H., Haq, M. I. U., & Bhatti, D. M. S. (2018) · ACM Computing Surveys · doi:10.1145/3178155 · Cited by 247
Statistical Issues and Assumptions of Phylogenetic Generalized Least Squares
Mundry, R. (2014) · Springer eBooks · doi:10.1007/978-3-662-43550-2_6 · Cited by 236
“A simple mean to detect collinearity is inspection of so-called variance inflation factors (VIF; Quinn and Keough 2002; Field 2005).”
BackgroundMethodInfluentialCaffarra, A., & Donnelly, A. (2010) · International Journal of Biometeorology · doi:10.1007/s00484-010-0386-1 · Cited by 231
“Data from the experiments were tested for deviance from normality and for the homogeneity of variance using Fligner-Killeen’s and Levene’s tests (Quinn and Keough 2002).”
MethodInfluentialRosell, J. A., Gleason, S. M., Méndez‐Alonzo, R., Chang, Y., & Westoby, M. (2013) · New Phytologist · doi:10.1111/nph.12541 · Cited by 233
“We fitted a nested ANOVA with random effects and calculated its variance components (Quinn & Keough, 2002).”
MethodNatural population dynamics and expansion of pathogenic clones of Staphylococcus aureus
Melles∗, D. C., Gorkink, R. F. J., Boelens, H. A. M., Snijders, S. V., Peeters, J. K., Moorhouse, M. J., van der Spek, P. J., van Leeuwen, W. B., Simons, G., Verbrugh, H. A., et al. (2004) · Journal of Clinical Investigation · doi:10.1172/jci23083 · Cited by 254
Kolb, A., Ehrlén, J., & ERIKSSON, O. (2007) · Perspectives in Plant Ecology Evolution and Systematics · doi:10.1016/j.ppees.2007.09.001 · Cited by 229
“Negative variance component estimates (encountered in one case) were converted to zero (Quinn and Keough, 2002).”
BackgroundTRANSGENERATIONAL PLASTICITY IN THE SEA: CONTEXT-DEPENDENT MATERNAL EFFECTS ACROSS THE LIFE HISTORY
Marshall, D. J. (2008) · Ecology · doi:10.1890/07-0449.1 · Cited by 231
“For the first and third field experiments, I used quasiF ratios (following Quinn and Keough 2002) to calculate the effects of maternal environment and density (where appropriate) because I had two replicate petri dishes from each colony.”
MethodLindenfors, P., Nunn, C. L., Jones, K. E., Cunningham, A. A., Sechrest, W., & Gittleman, J. L. (2007) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2006.00301.x · Cited by 236
“…the consequences and degree of nonlinearity, we included a quadratic term for citation counts in multivariate analyses (see below) and conducted statistical tests to determine whether inclusion of this term explained significant variation in the multivariate model (Quinn & Keough, 2002).”
The Cacti Microbiome: Interplay between Habitat-Filtering and Host-Specificity
Fonseca-García, C., Coleman‐Derr, D., Garrido, E., Visel, A., Tringe, S. G., & Partida‐Martínez, L. P. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.00150 · Cited by 240
Müller, J. C., & Brandl, R. (2009) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2009.01677.x · Cited by 227
Hydraulic microhabitats and the distribution of macroinvertebrate assemblages in riffles
Brooks, A. J., Haeusler, T., Reinfelds, I., et al. (2005) · Freshwater Biology · doi:10.1111/j.1365-2427.2004.01322.x · Cited by 226
“…partitioning was undertaken to determine the ‘independent’ correlation of each of the simple physical measures (velocity, depth and substrate roughness) to macroinvertebrate abundance and taxonomic richness (Chevan & Sutherland, 1991; MacNally, 1996, 2002; Chapter 16 Quinn & Keough, 2002).”
BackgroundMethodMatuszewski, S., Hall, M. J. R., Moreau, G., Schoenly, K. G., Tarone, A. M., & Villet, M. H. (2020) · International Journal of Legal Medicine · doi:10.1007/s00414-019-02074-5 · Cited by 251
“References to this table are listed in Electronic Supplementary Material Author(s) Date of publication Locality Animal model Major research focus Chapman and Sankey [1] 1955 England Rabbits Arthropod inventory; habitats Bornemissza [2] 1957 Australia Guinea pig Arthropod inventory; succession Reed [3] 1958 USA Dogs Ar…”
BackgroundReiskind, M., & Lounibos, L. (2009) · Medical and Veterinary Entomology · doi:10.1111/j.1365-2915.2008.00782.x · Cited by 230
“…(longevity under high and low humidities), we conducted a canonical correspondence analysis (CCA) using the three larval variables as predictors of adult longevity for the two humidity treatments on both species and for each species separately ( Quinn & Keogh, 2002; Sherry & Henson, 2005 ).”
MethodAre fast explorers slow reactors? Linking personality type and anti-predator behaviour
Jones, K. A., & Godin, J. J. (2009) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2009.1607 · Cited by 223
Hagan, H., Pouget, E. R., Jarlais, D. C. D., & Lelutiu‐Weinberger, C. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwn237 · Cited by 222
“Since the analysis included samples of only those individuals who had injected drugs, the intercept term should not be interpreted as the average HCV rate among unexposed persons (25).”
BackgroundZhao, J., Chen, S., Jiang, B., Ren, Y., Wang, H., Vause, J., & Yu, H. (2012) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2012.10.014 · Cited by 224
Kern, A., Barcza, Z., Marjanović, H., Árendás, T., Fodor, N., Bónis, P., Bognár, P., & Lichtenberger, J. (2018) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2018.06.009 · Cited by 225
Detection of alternative stable states in marine communities
Petraitis, P. S., & Dudgeon, S. (2004) · Journal of Experimental Marine Biology and Ecology · doi:10.1016/j.jembe.2003.12.026 · Cited by 223
“However, a design of perturbation treatment crossed with locations and replicate sites nested within locations, which is a partly nested design, has the same problems as univariate repeated measure designs (Quinn and Keough, 2002; Petraitis and Dudgeon, in press).”
BackgroundVariability in functional traits mediates plant interactions along stress gradients
Schöb, C., Armas, C., Guler, M., Prieto, I., & Pugnaire, F. I. (2013) · Journal of Ecology · doi:10.1111/1365-2745.12062 · Cited by 229
“For the five functional traits used as proxies for plant morphology, we applied a principal components analysis (PCA) with Varimax rotation (Quinn & Keough 2002) to reduce the number and multicollinearity of variables.”
MethodInvasions and niche width: does niche width of an introduced crayfish differ from a native crayfish?
Olsson, K., Stenroth, P., Nyström, P., et al. (2009) · Freshwater Biology · doi:10.1111/j.1365-2427.2009.02221.x · Cited by 221
Avian assemblage structure and domestic cat densities in urban environments
Sims, V., Evans, K. L., Newson, S. E., Tratalos, J. A., & Gaston, K. J. (2007) · Diversity and Distributions · doi:10.1111/j.1472-4642.2007.00444.x · Cited by 220
“Our analyses are not influenced by collinearity between log-transformed cat density and the amount of green space, as the tolerance factor for these variables was 0.73 which is much greater than the threshold value below which this becomes a concern (Quinn & Keough, 2002).”
BackgroundInfluentialHuman population density explains alien species richness in protected areas
Spear, D., Foxcroft, L. C., Bezuidenhout, H., & McGeoch, M. A. (2013) · Biological Conservation · doi:10.1016/j.biocon.2012.11.022 · Cited by 219
Effectiveness of recycled P products as P fertilizers, as evaluated in pot experiments
Cabeza, R. A., Steingrobe, B., Römer, W., & Claassen, N. (2011) · Nutrient Cycling in Agroecosystems · doi:10.1007/s10705-011-9454-0 · Cited by 217
“The fertilizers were considered main factors according to one-way ANOVA (Quinn and Keough 2002).”
MethodInfluentialBiostatistical Design and Analysis Using R: A Practical Guide
Logan, M. (2010) · doi:10.5281/zenodo.14822403 · Cited by 220
Seasonal distribution and interactions between plankton and microplastics in a tropical estuary
Lima, A. R. A., Barletta, M., & da Costa, M. F. (2015) · Estuarine Coastal and Shelf Science · doi:10.1016/j.ecss.2015.05.018 · Cited by 217
Whole‐Profile Soil Carbon Stocks: The Danger of Assuming Too Much from Analyses of Too Little
Kravchenko, A. N., & Robertson, G. P. (2011) · Soil Science Society of America Journal · doi:10.2136/sssaj2010.0076 · Cited by 216
DIFFERENCES IN SEED BIOLOGY OF ANNUAL PLANTS IN ARID LANDS: A KEY INGREDIENT OF THE STORAGE EFFECT
Facelli, J. M., Chesson, P., & Barnes, N. E. J. (2005) · Ecology · doi:10.1890/05-0304 · Cited by 212
“Because of the multiple comparisons we set the alpha value at P 5 0.01 (Quinn and Keough 2002).”
InfluentialEffects of landscape structure and land‐use intensity on similarity of plant and animal communities
Dormann, C. F., Schweiger, O., Augenstein, I., Bailey, D., Billeter, R., Blust, G. D., DeFilippi, R., Frenzel, M., Hendrickx, F., Herzog, F., et al. (2007) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2007.00344.x · Cited by 216
“In order to reduce collinearity between the different interaction terms, all explanatory variables were scaled to mean 0 and standard deviation of 1 prior to analysis (Quinn & Keough, 2002), but the final model was identical for scaled and unscaled models and only the latter are presented here.”
MethodPiggott, J. J., Townsend, C. R., & Matthaei, C. D. (2015) · Global Change Biology · doi:10.1111/gcb.12861 · Cited by 215
“To avoid potential collinearity problems arising from inclusion in the same model of this quadratic term and interaction terms of the two categorical factors with the continuous predictor temperature, temperature was centred (Quinn & Keough, 2002).”
BackgroundMethodInfluentialClimate change impacts on mismatches between phytoplankton blooms and fish spawning phenology
Asch, R. G., Stock, C. A. A., & Sarmiento, J. L. (2019) · Global Change Biology · doi:10.1111/gcb.14650 · Cited by 235
“(b) The difference in variance between the January to December and July to June years was significant at p 0.05 based on the Levene test for equality of variances (Quinn & Keough, 2002).”
MethodInfluentialBølling, A. K., Li, Y., Yttri, K. E., et al. (2006) · Particle and Fibre Toxicology · doi:10.1186/1743-8977-3-1 · Cited by 214
Metadata
- Authors
- Quinn, G. P., & Keough, M. J.
- Affiliations
- Monash University (AU)
- The University of Melbourne (AU)
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2002-03-21
- OpenAlex
- W1489838709
- Cited by
- 10,674
- References
- 0
- Citations by year
- 2026: 200 · 2025: 218 · 2024: 239 · 2023: 250 · 2022: 275 · 2021: 394 · 2020: 448 · 2019: 430 · 2018: 446 · 2017: 473 · 2016: 528 · 2015: 625 · 2014: 763 · 2013: 719 · 2012: 675
- FWCI
- 50.52
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Cambridge University Press eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- experimental design, statistical analysis, biology, hypothesis testing, Bayesian analysis, linear models, generalized linear models, logistic regression, analysis of variance, repeated measures, log-linear models, multivariate analysis, classification, ordination, exploratory data analysis, assumption checking
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