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Books on the topic 'Two-factor analysis of variance'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

MacFarland, Thomas W. Two-Way Analysis of Variance. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-2134-4.

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2

American Physical Therapy Association (1921- ). Division of Research and Education., ed. Design of research and analysis of data in the clinic: Introduction to factorial designs and analysis of variance. American Physical Therapy Association, Division of Research and Education, 1985.

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3

Jacques, Herman. Analyse de données qualitatives. Masson, 1986.

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4

Herman, Jacques. Analyse de données qualitatives. Masson, 1986.

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5

service), SpringerLink (Online, ed. Two-Way Analysis of Variance: Statistical Tests and Graphics Using R. Thomas W. MacFarland, 2012.

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6

Byrne, Barbara M. A primer of LISREL: Basic applications and programming for confirmatory factor analytic models. Springer-Verlag, 1989.

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7

Morrison, Donald F. Multivariate statistical methods. 3rd ed. McGraw-Hill, 1990.

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8

Bartholomew, David J. Latent variable models and factor analysis. 2nd ed. Arnold, 1999.

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9

Bartholomew, David J. Latent variable models and factor analysis. C. Griffin, 1987.

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10

Ganesalingam, S. Two group discrimination analysis using factor scores: Statistics. College of Sciences, Massey University, 1999.

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11

Bartholomew, David, Martin Knott, and Irini Moustaki. Latent Variable Models and Factor Analysis. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119970583.

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12

Heinen, Ton. Discrete latent variable models. Tilburg University Press, 1993.

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13

Loehlin, John C. Latent variable models: An introduction to factor, path, and structural analysis. 2nd ed. Lawrence Erlbaum Associates, 1992.

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14

Loehlin, John C. Latent variable models: An introduction to factor, path, and structural analysis. L. Erlbaum Associates, 1987.

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15

Niesing, Jan. Simultaneous component and factor analysis methods for two or more groups: A comparative study. DSWO Press, Leiden University, 1997.

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16

Bartholomew, David J. Latent variable models and factor analysis: A unified approach. 3rd ed. Wiley, 2011.

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17

Keppel, Geoffrey. Design and analysis: A researcher's handbook. 3rd ed. Prentice Hall, 1991.

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18

Keppel, Geoffrey. Design and analysis: A researcher's handbook. Prentice Hall, 1991.

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19

Saff, E. B., Douglas Patten Hardin, Brian Z. Simanek, and D. S. Lubinsky. Modern trends in constructive function theory: Conference in honor of Ed Saff's 70th birthday : constructive functions 2014, May 26-30, 2014, Vanderbilt University, Nashville, Tennessee. American Mathematical Society, 2016.

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20

Back, Kerry E. Mean-Variance Analysis. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0005.

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The mean‐variance frontier is characterized with and without a risk‐free asset. The global minimum variance portfolio and tangency portfolio are defined, and two‐fund spanning is explained. The frontier is characterized in terms of the return defined from the SDF that is in the span of the assets. This is related to the Hansen‐Jagannathan bound. There is an SDF that is an affine function of a return if and only if the return is on the mean‐variance frontier. Separating distributions are defined and shown to imply two‐fund separation and mean‐variance efficiency of the market portfolio.

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21

Greenfield, Thomas Barr. Systems Analysis in Education: A Factor Analysis and Analysis of Variance of Pupil Achievement. Hassell Street Press, 2021.

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22

Moore, David S., George P. McCabe, William M. Duckworth, and Stanley L. Sclove. The Practice of Business Statistics Companion Chapter 15: Two-Way Analysis of Variance. W. H. Freeman, 2002.

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23

Lin, Wen-Ying. Robustness of two multivariate tests to variance-covariance heteroscedasticity and nonnormality when total-sample-size-to-variable ratio is small. 1991.

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24

Byrne, Barbara M. Primer of LISREL: Basic Applications and Programming for Confirmatory Factor Analytic Models. Springer, 2012.

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25

Coates, David. The effects of clusters on the utility of factor analysis: The implications of systematic interrater variance for the analysis of students' evaluations of teaching. Loughborough University Business School, 1997.

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26

Miksza, Peter, and Kenneth Elpus. Design and Analysis of Experimental Research I. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199391905.003.0008.

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This chapter builds on the previous chapter by elaborating from theories of causal knowledge presented earlier to practical considerations for the design, execution, and analysis of randomized experiments and randomized controlled trials in music education research. The straightforward statistical analysis of the two-group experimental designs is explained through the t test. The analysis of variance technique is explained for the analysis of experimental and quasi-experimental data involving more than two groups. The chapter closes with a discussion of the analysis of data arising from experi

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27

Stoolmiller, Mike. An Introduction to Using Multivariate Multilevel Survival Analysis to Study Coercive Family Process. Edited by Thomas J. Dishion and James Snyder. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199324552.013.27.

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Multivariate multilevel survival analysis is introduced for studying hazard rates of observed emotional behavior relevant for coercion theory. Finite time sampling reliability (FTSR) and short-term retest reliability (STRR) across two occasions (sessions) of observation during structured problem-solving tasks several weeks apart were determined for hazard rates of emotional behaviors for parent–child dyads. While FTSR was high (.80–.96), STRR was low (.16–.65), suggesting that emotional behaviors in the context of parent–child social interaction are not very stable over a period of several wee

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28

Rahat, Gideon, and Ofer Kenig. A Cross-National Analysis of Political Personalization. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198808008.003.0009.

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The chapter presents an integrated cross-national analysis of political personalization in all our twenty-six countries. The two indicators of personalization online stand apart in terms of the incidents of depersonalization. An examination of the relationship between the three dimensions finds personalization especially in the institutional realm. In the other two dimensions, media and behavior, most cases are of personalization, but many indicate no trend or depersonalization. A comparison by country illustrates that, except for the cases of extreme personalization in Italy and Israel and a

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29

Knott, Martin, Irini Moustaki, and David J. Bartholomew. Latent Variable Models and Factor Analysis. Wiley & Sons, Incorporated, John, 2011.

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30

Haig, Brian D. Exploratory Factor Analysis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190222055.003.0006.

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Chapter 6 argues that exploratory factor analysis is an abductive method of theory generation that exploits a principle of scientific inference known as the principle of the common cause. Factor analysis is an important family of multivariate statistical methods that is widely used in the behavioral and social sciences. The best known model of factor analysis is common factor analysis, which has two types: exploratory factor analysis and confirmatory factor analysis. A number of methodological issues that arise in critical discussions of exploratory factor analysis are considered. It is sugges

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31

Loehlin, John C. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis. Taylor & Francis Group, 2004.

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32

Latent Variable Models and Factor Analysis (Statistical Monograph). Hodder Arnold, 1987.

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33

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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34

Loehlin, John C., and A. Alexander Beaujean. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis, Fifth Edition. Taylor & Francis Group, 2017.

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35

Loehlin, John C., and A. Alexander Beaujean. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis, Fifth Edition. Taylor & Francis Group, 2016.

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36

Loehlin, John C., and A. Alexander Beaujean. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis, Fifth Edition. Taylor & Francis Group, 2016.

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37

Loehlin, John C., and A. Alexander Beaujean. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis, Fifth Edition. Taylor & Francis Group, 2016.

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38

Loehlin, John C., and A. Alexander Beaujean. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis, Fifth Edition. Taylor & Francis Group, 2016.

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39

Loehlin, John C. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis, Fifth Edition. Taylor & Francis Group, 2017.

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40

Elwood, Mark. Combining results from several studies: systematic reviews and meta-analyses. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682898.003.0009.

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This chapter explains systematic reviews, the PRISMA format, and meta-analysis. It discusses publication bias, outcome reporting bias, funnel plots, the issue of false positive results in small studies, along with search strategies, electronic databases, PubMed, and the Cochrane collaboration. It discusses the assessment of quality, risks of bias, limitations of meta-analysis, heterogeneity testing, effect modification, and meta-regression methods. In part two, it explains statistical methods for meta-analyses are presented, including the Mantel-Haenszel and Peto methods for individual patient

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41

Loehlin, John C. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis (Latent Variable Models: An Introduction to). 4th ed. Lawrence Erlbaum, 2003.

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42

Loehlin, John C. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis (Latent Variable Models: An Introduction to). 4th ed. Lawrence Erlbaum, 2003.

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43

Knott, Martin, and David J. Bartholomew. Latent Variable Models and Factor Analysis: Kendall's Library of Statistics 7. Wiley & Sons, Incorporated, John, 1999.

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44

Latent variable models: An introduction to factor, path, and structural analysis. 3rd ed. Lawrence Erlbaum, 1998.

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45

Latent variable models: An introduction to factor, path, and structural equation analysis. 4th ed. L. Erlbaum Associates, 2004.

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46

Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis. Routledge, 2017.

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47

Jackman, Simon. Measurement. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0006.

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This article shows that the words ‘behavioural’ and ‘behaviour’ turn out to be better measures as judged by tests of criterion and convergent validity. It specifically discusses measurement problems. Further, it pertains to statistical models that link latent variables and their observed indicators as measurement models. The success of measurement — the quality of the inferences provided by a measurement model — is usually assessed with reference to two key concepts: validity and reliability. The distinct uses of measures of latent variables are reported. The article then deals with the costs

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48

Hromadka, Theodore V. Two-Dimensional Potential Analysis Using Boundary Elements / Two-Dimensional Elastostatic Analysis Using Boundary Elements / Complex Variable Boundary Elements. WIT Press, 1986.

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49

Boisvert, Donald L., and Jay Emerson Johnson, eds. Queer Religion. ABC-CLIO, LLC, 2011. http://dx.doi.org/10.5040/9798216983507.

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Queer Religion provides a systematic and detailed overview of the challenges and issues that the intersections of religion, same-sex desire, and gender variance have generated, both now and in the past. It focuses upon the development of these areas of overlap through three distinct historical periods: modern religious history, LGBT liberation movements, and the emergence of queer theory and analysis. This two-volume collection of eclectic essays investigates the experiences of queer people and religion, providing a broad, unique, and invaluable analysis of this important cultural and theologi

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50

Boisvert, Donald L., and Jay Emerson Johnson, eds. Queer Religion. ABC-CLIO, LLC, 2011. http://dx.doi.org/10.5040/9798216983491.

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Queer Religion provides a systematic and detailed overview of the challenges and issues that the intersections of religion, same-sex desire, and gender variance have generated, both now and in the past. It focuses upon the development of these areas of overlap through three distinct historical periods: modern religious history, LGBT liberation movements, and the emergence of queer theory and analysis. This two-volume collection of eclectic essays investigates the experiences of queer people and religion, providing a broad, unique, and invaluable analysis of this important cultural and theologi

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