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Analysis Of Variance: Between-groups Designs / Alan J. Klockars -- Analysis Of Variance: Repeated Measures Designs / Lisa M. Lix And H. J. Keselman -- Canonical Correlation Analysis / Xitao Fan And Timothy R. Konold -- Cluster Analysis / Dena A. Pastor -- Correlation And Other Measures Of Association / Jason W. Osborne -- Discriminant Analysis / Carl J. Huberty -- Effect Sizes And Confidence Intervals / Geoff Cumming And Fiona Fidler -- Factor Analysis: Exploratory And Confirmatory / Deborah L. Bandalos And Sara J. Finney -- Generalizability Theory / Amy Hendrickson And Ping Yin -- Hierarchical Linear Modeling / D. Betsy Mccoach -- Interrater Reliability And Agreement / William T. Hoyt -- Item Response Theory / R.j. De Ayala -- Latent Class Analysis / Karen M. Samuelsen And C. Mitchell Dayton -- Latent Growth Curve Models / Kristopher J. Preacher -- Latent Translation Analysis / David Rindskopf -- Latent Variable Mixture Models / Gitta Lubke -- Logistic Regression / Ann A. O'connell And K. Rivet Amico -- Log-linear Analysis / Ronald C. Serlin And Michael A. Seaman -- Meta-analysis / S. Natasha Beretvas -- Multidimensional Scaling / Mark L. Davison, Cody S. Ding, And Se-kang Kim -- Multiple Regression / Ken Kelley And Scott E. Maxwell -- Multitrait-multimethod Analysis / Keith F. Widaman -- Multivariate Analysis Of Variance / Stephen Olejnik -- Power Analysis / Kevin R. Murphy -- Reliability And Validity Of Instruments / Thomas R. Knapp And Ralph O. Mueller -- Research Design / Sharon Anderson Dannels -- Single Subject Design And Analysis / Andrew L. Egel And Christine H. Barthold -- Structural Equation Modeling / Ralph O. Mueller And Gregory R. Hancock -- Structural Equation Modeling: Multisample Covariance And Mean Structures / Richard G. Lomax -- Survey Sampling, Administration, And Analysis / Laura M. Stapleton -- Survival Analysis / Paul D. Allison. Editors, Gregory R. Hancock, Ralph O. Mueller. Includes Bibliographical References.
This volume investigates the core question of how researchers and reviewers can effectively evaluate, interpret, and apply complex quantitative methodologies within social science research. Editors Gregory R. Hancock and Ralph O. Mueller compile contributions from leading experts to provide a comprehensive framework for understanding the rigor and validity of various statistical techniques. The text serves as a technical manual designed to bridge the gap between theoretical statistical models and their practical application in peer-reviewed research.
What You Will Find
Experts and academics frequently cite this volume as a foundational reference for graduate students and researchers navigating the complexities of quantitative social science. Readers often note the high density of the technical prose, which requires a solid background in statistics to fully utilize the provided methodologies.
Page Count:
448
Publication Date:
2010-01-01
Publisher:
Routledge
ISBN-10:
0203861558
ISBN-13:
9780203861554
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