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Books on the topic 'Analysis of Varience (ANOVA)'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

ANOVA: An analysis of variance primer. F.E. Peacock Publishers, 1994.

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2

ANOVA: Repeated measures. Sage Publications, 1992.

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3

Rutherford, Andrew, and Andrew Rutherford. ANOVA and ANCOVA: A GLM approach. 2nd ed. Wiley, 2011.

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4

Introducing ANOVA and ANCOVA: A GLM approach. SAGE, 2001.

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5

Jackson, Sally Ann. Random factors in ANOVA. Sage Publications, 1994.

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6

Rutherford, Andrew. ANOVA and ANCOVA: A GLM approach. 2nd ed. Wiley, 2011.

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7

S, Fidell Linda, ed. Experimental designs using ANOVA. Thomson/Brooks/Cole, 2007.

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8

M, Borror Connie, and Montgomery Douglas C, eds. Design and analysis of gauge R&R studies: Making decisions with confidence intervals in random and mixed ANOVA models. Society for Industrial Applied Mathematics, 2005.

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9

Scott Jones, Julie. Learn to Use Factorial Analysis of Variance (ANOVA) in SPSS With Data From the English Health Survey (Teaching Dataset) (2002). SAGE Publications Ltd., 2019. http://dx.doi.org/10.4135/9781526485786.

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10

Scott Jones, Julie. Learn to Use Factorial Analysis of Variance (ANOVA) in R With Data From the English Health Survey (Teaching Dataset) (2002). SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526498694.

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11

Harris, Richard J. Anova an Analysis of Variance Primer. F.E. Peacock Publishers, 1994.

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12

Smoothing Spline ANOVA Models. Springer, 2002.

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13

Gu, Chong. Smoothing Spline ANOVA Models. Springer, 2013.

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14

Gu, Chong. Smoothing Spline ANOVA Models. Springer, 2015.

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15

ANOVA For The Behavioural Sciences Researcher. Lawrence Erlbaum Associates, 2005.

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16

Cardinal, Rudolf N., and Michael R. F. Aitken. ANOVA For The Behavioural Sciences Researcher. Lawrence Erlbaum Associates, 2005.

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17

Muller, Keith E., and Bethel A. Fetterman. Regression and ANOVA : An Integrated Approach Using SAS Software. WA (Wiley-SAS), 2003.

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18

Regression and ANOVA: An Integrated Approach Using SAS Software. SAS Publishing, 2002.

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19

Regression Anova And The General Linear Model A Statistics Primer. Sage Publications (CA), 2013.

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20

Goos, Peter, and David Meintrup. Statistics with JMP: Hypothesis Tests, ANOVA and Regression. Wiley & Sons, Incorporated, John, 2016.

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21

Statistical Modeling, Linear Regression and ANOVA: A Practical Computational Perspective. Lulu.com, 2018.

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22

Paolella, Marc S. Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH. Wiley & Sons, Incorporated, John, 2018.

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23

Effect Size for ANOVA Designs (Quantitative Applications in the Social Sciences). Sage Publications, Inc, 1999.

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24

Girden, Ellen R. ANOVA: Repeated Measures (Quantitative Applications in the Social Sciences). Sage Publications, Inc, 1991.

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25

Miksza, Peter, and Kenneth Elpus. Design and Analysis of Experimental Research II. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199391905.003.0009.

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This chapter introduces the reader to more possibilities for thinking about causal questions and for laying the foundational concepts necessary for conducting data analyses that correspond to more complex experimental designs. The discussion of experimental design types presented in chapter 8 is expanded to include within-subjects designs, factorial designs, mixed designs, and designs for multivariate outcomes. Prototypical examples of each design type are presented along with the typical analysis tools used for testing the associated experimental hypotheses. Hypothetical examples of research

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26

Ryan, Carey S., Gary H. McClelland, and Charles M. Judd. Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond, Third Edition. Taylor & Francis Group, 2017.

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27

Ryan, Carey S., Gary H. McClelland, and Charles M. Judd. Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond, Third Edition. Taylor & Francis Group, 2017.

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28

Ryan, Carey S., Gary H. McClelland, and Charles M. Judd. Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond, Third Edition. Taylor & Francis Group, 2017.

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29

Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond, Third Edition. Taylor & Francis Group, 2017.

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30

Dario, Basso, ed. Permutation tests for stochastic ordering and ANOVA: Theory and applications with R. Springer, 2009.

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31

Dario, Basso, ed. Permutation tests for stochastic ordering and ANOVA: Theory and applications with R. Springer, 2009.

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32

Fidell, Linda S., and Barbara G. Tabachnick. Experimental Designs Using ANOVA (with Student Suite CD-ROM) (Duxbury Applied Series). Duxbury Press, 2006.

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33

Tukey, John Wilder. The Collected Works of John W. Tukey: Factorial & Anova (Tukey, John Wilder//Collected Works of John W Tukey). Wadsworth Publishing Company, 1992.

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34

Veech, Joseph A. Habitat Ecology and Analysis. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198829287.001.0001.

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Habitat is crucial to the survival and reproduction of individual organisms as well as persistence of populations. As such, species-habitat relationships have long been studied, particularly in the field of wildlife ecology and to a lesser extent in the more encompassing discipline of ecology. The habitat requirements of a species largely determine its spatial distribution and abundance in nature. One way to recognize and appreciate the over-riding importance of habitat is to consider that a young organism must find and settle into the appropriate type of habitat as one of the first challenges

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35

Applied plant science experimental design and statistical analysis using the SAS® OnDemand for Academics. CABI, 2021. http://dx.doi.org/10.1079/9781789249927.0000.

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Abstract The correct design, analysis and interpretation of plant science experiments is imperative for continued improvements in agricultural production worldwide. The enormous number of design and analysis options available for correctly implementing, analyzing and interpreting research can be overwhelming. Statistical Analysis System (SAS®) is the most widely used statistical software in the world and SAS® OnDemand for Academics is now freely available for academic insttutions. This is a user-friendly guide to statistics using SAS® OnDemand for Academics, ideal for facilitating the design a

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36

Miles, Jeremy. General and generalised linear models. Oxford University Press, 2015. http://dx.doi.org/10.1093/med:psych/9780198527565.003.0017.

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This chapter discusses general and generalised linear models (GLM and GLZ respectively). It outlines GLMs (mean, properties of GLMs and the mean), samples and populations, comparison of two groups of data, multiple regression and the GLM, analysis of variance (ANOVA) and the GLM, GLM in SPSS, and the GLZ).

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