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Statistics bibliography D - stats
Andersen, B. (1990). Methodological errors in medical research. Blackwells Publishers, Oxford, UK.
Anderson, M.J. & Ter braak, C.J.F. (2003). Permutation tests for multi-factorial analysis of variance. Journal of Statistical Computation and Simulation 73 (2), 85-113.
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Anderson, V.L. & McLean, R.A. (1974). Restriction errors: Another dimension in teaching experimental statistics. The American Statistician 28
145-152.
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Bailey, R.A. (2008). Design of comparative experiments. Cambridge University Press. 348 pp.
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Bauer, D.J. & Curran, P.J. (2006). Probing interactions in fixed and multilevel regression: Inferential and graphical techniques.
Multivariate Behavioral Research 40 (3), 373-400.
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Beaupre, S.J. & Dunham, A.E. (1995). A comparison of ratio-based and covariance analyses of a nutritinal data set. Functional Ecology 9 (6), 876-880.
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Beckerman, H. et al. (2001). Smallest real difference, a link between reproducibility and responsiveness Quality of Life Research 10 (7), 571-578.
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Bennington, C.C.. & Thayne, W.V. (1994). Use and misuse of mixed model analysis of variance in ecological studies. Ecology 75 (3), 717-722 .
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Bliese, P.D. & Hanges, P.J. (2004). Being both too liberal and too conservative: The perils of treating grouped data
as though they were independent. Organizational Research Methods 7 (4), 400-417.
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Caudle, R.M. & Williams, G.M. (1993). The misuse of analysis of variance to detect synergy in combination drug studies. Pain 55 (3), 313-317 .
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Ceyhan, E. & Goad, C.L. (2009). A comparison of analysis of covariate-adjusted residuals and analysis of covariance. Communications in Statistics - Simulation and Computation 38 (10), 2019 - 2038.
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Field, A. (1998). A bluffer's guide to ... sphericity. The British Psychological Society: Mathematical, Statistical & Computing Section Newsletter 6, 13-22.
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Fitzmaurice, G.M. & Ravichandran, C. (2008). Statistical primer for cardiovascular research. A Primer in Longitudinal Data Analysis. Circulation 118, 2005-2010.
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Fleiss, J.L. & Tanur, J.M. (1973). The analysis of covariance in psychopathology. pp 509-527 In: Hammer, M. et al. (Eds.) Psychpathology: Contributions from the social, behavioral, and biological sciences. Wiley, New York.
Fraas, J.W. & Newman, I. (2005). The use of the Johnson-Neyman confidence bands and multiple regression models to investigate interaction effects: important tools for educational researchers and program evaluators. Multiple Linear Regression Viewpoints 24, 14-24.
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Freckleton, R.F. (2002). On the misuse of residuals in ecology: regression of residuals vs. multiple regression. Journal of Animal
Ecology 71 (3), 542-545.
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Frison, L. & Pocock, S.J. (2007) Repeated measures in clinical trials: Analysis using mean summary statistics and its implications for design . Statistics in Medicine 11 (13), 1685-1704.
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Fry, J.C. (Ed) (1993). Biological data analysis: a practical approach. Oxford University Press, Oxford. 448 pp.
Gelman, A. (2005). Analysis of variance - Why is it more important than ever. The Annals of Statistics 33 (1), 1-53.
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German, R.Z. et al. (2008).
Variation in EMG activity: a hierarchical approach. Integrative and Comparative Biology 48 (2), 283-293.
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Green, S. et al. (2002). Factorial design considerations. Journal of Clinical Oncology 20 (16), 3424-3430.
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Greenwood, J.J.D. (1994). Statistical analysis of experiments conducted at multiple sites. Oikos 69 (2), 334.
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Gueorguieva, R. & Krystal, J.H. (2004) Move over ANOVA. Progress in analyzing repeated-measures data and its reflection in papers published in the Archives of General Psychiatry. Archives of General Psychiatry 61, 310-317.
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Hand, D.J. & Taylor, C.C.. Multivariate analysis of variance and repeated measures: A practical approach for behavioural scientists. Chapman & Hall, London. 262 pp.
Hayes, A.F. & Matthes, J. (2009). Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. Behavior Research Methods 41 (3), 924-936.
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Hewitt, J.E. et al. (2001). Assessing environmental impacts: effects of spatial and temporal variability at likely impact scales. Ecological Applications 11 (5), 1502-1516.
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Hines, W. G. S. (1996). Pragmatics of pooling in ANOVA tables. The American Statistician 50 (2), 127-139.
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Horton, D.R. & Redak, R.A. (1993) Further comments on analysis of covariance in insect dietary studies. Entomologia Experimentalis et Applicata 69 (3), 263-275.
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Howell, D.C. (2002). Fundamental statistics for the behavioral sciences. 6th Edn. Wadsworth.
Huitema, B.E. (1980) The analysis of covariance and alternatives. Wiley, New York.
[not available in full on line]
Jackson, S. & Brashers, D.E. (Eds) (1994). Random factors in ANOVA (Quantitative applications in the social sciences). Sage Publications. 80 pp.
Jamieson, J. (2005). Analysis of covariance (ANCOVA) with difference scores. International Journal of Psychophysiology 52 (3), 277-283.
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Janky, D.G. (2000).
Sometimes pooling for analysis of variance hypothesis tests: A review and study of a split-plot model. The American Statistician 54 (4), 269-279.
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Jenkins, S.H. (2002).
Data pooling and type I errors: a comment on Leger & Didrichsons. Animal Behaviour 63, F9-F11.
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Kahler, E. et al. (2008). A parametric analysis of ordinal quality-of-life data can lead to erroneous results. Journal of Clinical Epidemiology 61 (5), 475-480.
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Keselman, K.J. (1998) Testing treatment effects in repeated measures designs: An update for psychophysiological researchers. Psychophysiology 35, 470-478.
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Keselman, H.J. et al. (2000).
Testing treatment effects in repeated measures designs: trimmed means and bootstrapping. 53 (2), 175-191.
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Keselman, H.J. et al. (2001). The analysis of repeated measures designs: A review . British Journal of Mathematical and Statistical Psychology 54 (1), 1-20.
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Kolasa, J. & Rollo, D.C. (1991). The heterogeneity of heterogeneity: a glossary. pp 1-23 in Kolasa, J & Pickett, S.T.A. (eds). Ecological heterogeneity. Springer Verlag, New York.
Kowalski, C.J. et al. (1994). ANCOVA for nonparallel slopes: the Johnson-Neyman technique. International Journal of Bio-Medical Computing 37, 273-286.
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Kromrey, J.D. & Dickinson, W.B. (1996).
Detecting unit of analysis problems in nested designs: Statistical power and Type I error rates of the F test for groups-within-treatments effects. Educational and Psychological Measurement 56 (2), 215-231.
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Kroodsma, D.E. et al. (2001). Pseudoreplication in playback experiments, revisited a decade later . Animal Behaviour 61 (5), 1029-1033. Read
Kusuoka, H. & Hoffman, J.I.E. (2002). Advice on statistical analysis for circulation research. Circulation Research 91, 662-671.
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Langsrud, Ø (2003). ANOVA for unbalanced data: Use Type II instead of Type III sums of squares. Statistics and Computing 13, 163-167.
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Lee, C.J. et al (2008). Statistical analysis of field trials with changing treatment variance. Agronomy Journal 100 (3), 1311-1320.
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Lee, Y. & Nelder, J. (2003). False parsimony and its detection with GLMs. Journal of Applied Statistics 30 (5), 477 - 483.
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Leger, D.W. & Didrichsons, I.A. (1998).
An assessment of data pooling and some alternatives. Animal Behaviour 48, 823-832.
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Lentner, M. et al. (1989). The efficiency of blocking: how to use MS(Blocks)/MS(Error) correctly.The American Statistician 43 (2), 106-108.
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Lew, M. (2007). Good statistical practice in pharmacology. Problem 2. British Journal of Pharmacology 152, 299-303.
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Liermann, M et al. (2004). Random denominators and the analysis of ratio data. Environmental and Ecological Statistics 11 (1), 55-71.
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Littell, R.C.. et al. (1998). Statistical analysis of repeated measures data using SAS procedures. Journal of Animal Science 76 (4), 1216-1231.
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Littell, R.C. (2002). Analysis of unbalanced mixed model data: A case study comparison of ANOVA versus REML/GLS. Journal of Agricultural, Biological, and Environmental Statistics 7 (4), 472-490.
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Lively, C.M. & McKone, M.J. (1994).
Choosing an appropriate ANOVA for experiments conducted at few sites. Oikos
69 (2), 335.
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Logan, M. (2010). Biostatistical design and analysis using R: a practical guide. Wiley-Blackwell.
Looney, S.W. & Stanley, W.B. (1989). Exploratory repeated measures analysis for two or more groups: review and update. American Statistician 43 (4), 220-225.
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Loughin, T. M. (2007). Improved experimental design and analysis for long-term experiments. Analysis of Unreplicated Experiments (Symposium) Crop Science 46, 2492-2502.
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McCall, R.B. and Appelbaum, M.I. (1973) Bias in the analysis of repeated-measures designs: Some alternative approaches. Child Development 44 (3), 401-415.
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McHugh, R.B. (1964). Need the randomized block design be replicated. The Journal of Experimental Education 33 (2), 169-174.
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McKone, M.J. & Lively, C.M. (1993). Statistical analysis of experiments conducted at multiple sites. Oikos 67 (1), 184-186.
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McCoy, M.W. et al. (2006). Size correction: comparing morphological traits among populations and environment. Oecologia 148, 547-554.
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McLean, R.A. & Anderson. V.L. (1980). Note on a clarification of restriction errors. Department of Statistics, Mimeograph series #80-19, Purdue University.
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Mead, R. et al. (2002). Statistical Methods in Agriculture and Experimental Biology 3rd Edn. Chapman & Hall. 488 pp.
Meek, G.E. et al. (2007). Small F-ratios: Red flags in the linear model. Journal of Data Science 5, 199-215.
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Miller, G.A. & Chapman, J.P. (2001)
Misunderstanding analysis of covariance. Journal of Abnormal Psychology 110 (1), 40-48.
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Montgomery, A.A. (2003). Design, analysis and presentation of factorial randomised controlled trials. BMC Medical Research Methodology 3, 26.
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Neter, J. et al. (1985) Applied linear regression models. Irwin, Homewood, Illinois.
[not available in full on line]
Newman, J.A. et al. (1997). Blocking factors and hypothesis tests in ecology: Is your statistics text wrong? Ecology 78 (5), 1312-1320. Read
Olejnik, S.F. & Algina, J. (1985). A review of nonparametric alternatives to analysis of covariance. Evaluation Review 9 (1), 51-83.
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O'Neill, M.E. & Mathews, K.L. (2002). Levene tests of homogeneity of variance for general block and treatment designs. Biometrics 58 (1), 216-224.
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Ottenbacher, K.J. (1991). Interpretation of interaction in factorial analysis of variance design. Statistics in Medicine 10 (10), 1565-1571.
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Palmer, A.A. & Airey, D.C. (2003). Inappropriate choice of the experimental unit leads to dramatic overestimation of the significance of quantitative trait loci for prepulke inhibition and startle response in recombinant congenic mice. Neuropsychopharmacology 28, 818.
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Paterson, S. & Lello, J. (2003). Mixed models: getting the best use of parasitological data. TRENDS in Parasitology 19 (8), 370-375.
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Patterson. H.D. (1951). Change-Over Trials. Journal of the Royal Statistical Society. Series B (Methodological) 13 (2), 256-271.
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Payne, R.W. (2006). New and traditional methods for the analysis of unreplicated experiments. Analysis of Unreplicated Experiments (Symposium) Crop Science 46, 2476-2481.
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Perry, J.N. et al. (1980). Latin Square designs in field experiments involving insect sex attractants. Ecological Entomology 5 (4), 385-396.
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Piepho, H.-P. et al. (2009). Data transformation in statistical analysis of field trials with changing treatment variance. Agronomy Journal 101, 865-869.
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Pilla, R.S. (2005). Statistical analysis of modified complete randomized designs: applications to chemo-orientation studies. The Journal of Experimental Biology 208, 1267-1276.
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Preacher, K.J. et al. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics 31 (4), 437-448.
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Quené, H. & van den Bergh, H. (2004) On multi-level modeling of data from repeated measures designs: a tutorial. Speech Communication 43 (1-2), 103-121.
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Quinn, G.P. & Keough, M.J. (2002).
Experimental design and data analysis for biologists. Cambridge University Press, Cambridge, UK. 537 pp.
Raubenheimer, D & Simpson, S.J. (1992). Analysis of covariance: an alternative to nutritional indices. Entomologia Experimentalis et Applicata 62 (3), 221-231.
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Riley, J. & Edwards, P. (2008). Statistical aspects of aquaculture research: pond variability and pseudoreplication. Aquaculture Research 29 (4), 281 - 288.
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Rouanet, H. & Lépine, D. (1970). Comparison between treatments in a repeated-measurement design: Anova and multivariate methods. The British Journal of Mathematical and Statistical Psychology 23, 147-163.
Samuels, M.L. et al. (1988). Are blocks different from random factors? Technical Report #88-26, Purdue University and Cornell University.
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Scariano, S. M. & Davenport, J. M. (1987). The effects of violations of independence in the oneway ANOVA. The American Statistician 41 (2), 123-129.
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Schaaljea, G.B. & Despaina, D.J. et al. (1966). Robustness of homogeneity of variance tests for randomized complete block data. Communications in Statistics - Simulation and Computation 25 (4), 961 - 977.
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Schwarz, C.J. (1993).
The mixed-model ANOVA: The truth, the computer packages, the books. Part I: Balanced data . The American Statistician 47 (1), 48-59.
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Senn, S. (2001)
Change from baseline and analysis of covariance revisited. Statistics in Medicine 25 (24), 4334 - 4344.
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Serrano, E. et al. (2008). A half a century of measuring ungulate body condition using indices: is it time for a change? European Journal of Wildlife Research 54 (4), 675-680.
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Shen, J. (1995). On choosing an appropriate ANOVA for ecological experiments. Oikos 73 (3), 404.
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Tamhane, A.C. (2009). Statistical analysis of designed experiments: Theory and applications. Wiley, New York. 679 pp.
Van Breukelen, G.J.P. (2006). ANCOVA versus change from baseline had more power in randomized studies and more bias in nonrandomized studies. Journal of Clinical Epidemiology 59 (9), 920-925.
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Vanderburgh, P.M. et al. (1998). Nonparallel slopes using analysis of covariance for body size adjustment may reflect inappropriate modeling. Measurement in Physical Education and Exercise Science 2 (2), 127 - 135.
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Vasey, M.W. & Thayer, J.F. (1987) The continuing problem of false positives in repeated measures ANOVA in psychophysiology: A multivariate solution. Psychophysiology 24 (4), 479 - 486.
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Vickers, A.J. (2001). The use of percentage change from baseline as an outcome in a controlled trial is statistically inefficient: a simulation study. BMC Medical Research Methodology 1: 6
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Vickers, A.J. (2005). Analysis of variance is easily misapplied in the analysis of randomized trials: A critique and discussion of alternative statistical approaches. Psychosomatic Medicine 67, 652-655.
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Vickers, A.J. (2005). Parametric versus non-parametric statistics in the analysis of randomized trials with non-normally distributed data. BMC Medical Research Methodology 5: 35.
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Vickers, A.J. & Altman, D.G. (2001). Analysing controlled trials with baseline and follow up measurements. BMJ 323, 1123-1124 (10 November).
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Wilcox, R. R. (1987). Pairwise comparisons of J independent regression lines over a finite interval, simultaneous pairwise comparison
of their parameters, and the Johnson-Neyman technique. British Journal of Mathematical and Statistical Psychology 40, 80-93.
Wilcox, R.R. et al. (2000) Repeated measures ANOVA: Some new results on comparing trimmed means and means. British Journal of Mathematical and Statistical Psychology 53 (1), 69-82.
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Wildt, A.R. & Ahtola, O.T. (1978). Analysis of covariance . Sage Publications. 91 pp.
Wilk, M.B. & Kempthorne, O. (1955). Fixed, mixed and random models. Journal of the American Statistical Association 50 (272), 1144-1167.
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