Quantitative Research in Psychology (SAGE Benchmarks in Psychology)

Quantitative Research in Psychology (SAGE Benchmarks in Psychology)

By: Jeremy Miles (editor), Brian Stucky (editor)Hardback

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Description

Quantitative psychology is a branch of psychology developed using certain methods and approaches which are designed to answer empirical questions, such as the development of measurement models and factor analysis. While quantitative psychology is often associated with the use of statistical models and psychological measurement research methods, this five volume set draws together the key conceptual and methodological techniques and addresses each research question at length. Each volume is accompanied by an introduction which contextualises the subject area, giving an understanding of established theories and how they are continuing to develop in one of the most fundamental and broadly researched psychological fields. These volumes are an excellent resource for academics and scholars who will benefit from the framing provided by the editorial introduction and overview, and will also appeal to advanced students and professionals studying or using quantitative psychological methods in their research. Volume One: Statistical hypothesis testing and power Volume Two: Measurement Volume Three: Research Design and sampling Volume Four: Statistical Tests Volume Five: Complex Models

Contents

VOLUME ONE: STATISTICAL HYPOTHESIS TESTING AND POWER What Is Statistical Significance? - Ralph Tyler Bayesian Statistical Inference for Psychological Research - Ward Edwards, Harold Lindman and Leonard Savage Statistical Difficulties of Detecting Interactions and Moderator Effects - Gary McClelland and Charles Judd The Earth Is Round (p < 0.05) - Jacob Cohen Power Analysis and Determination of Sample Size for Covariance Structure Modeling - Robert MacCallum, Michael Browne and Hazuki Sugawara Computing Contrasts, Effect Sizes, and Counternulls on Other People's Published Data: General Procedures for Research Consumers - Ralph Rosnow and Robert Rosenthal Statistical Significance Testing and Cumulative Knowledge in Psychology: Implications for the Training of Researchers - Frank Schmidt The Appropriate Use of Null Hypothesis Significance Testing - Robert Frick Controlling the Rate of Type I Error over a Large Set of Statistical Tests - H.J. Keselman, Robert Cribbie and Burt Holland Hypothesis Testing and Theory Evaluation at the Boundaries: Surprising Insights from Bayes's Theorem - David Trafimow Mindless Statistics - Gerd Gigerenzer An Alternative to Null-Hypothesis Significance Tests - Peter Killeen False-Positive Psychology Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant - Joseph Simmons, Leif Nelson and Uri Simonsohn VOLUME TWO: MEASUREMENT The Proof and Measurement of Association between Two Things - C. Spearman A Method of Scaling Psychological and Educational Tests - Louis Thurstone Multiple Factor Analysis - Louis Thurstone Coefficient Alpha and the Internal Structure of Tests - Lee Cronbach The Relation of Test Score to the Trait Underlying the Test - Frederic Lord Construct Validity in Psychological Tests - L. Cronbach and P. Meehl Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix - Donald Campbell and Donald Fiske The Axioms and Principal Results of Classical Test Theory - Melvin Novick A General Approach to Confirmatory Maximum Likelihood Factor Analysis - K. Joereskog Intraclass Correlations: Uses in Assessing Rater Reliability - Patrick Shrout and Joseph Fleiss Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM Algorithm - R. Darrell Bock and Murray Aitkin A Taxonomy of Item Response Models - David Thissen and Lynne Steinberg The New Rules of Measurement - Susan Embretson The Concept of Validity - Denny Borsboom, Gideon Mellenbergh and Jaap van Heerden On the Use, the Misuse, and the Very Limited Usefulness of Cronbach's Alpha - Klaas Sijtsma A Two-Tier Full-Information Item Factor Analysis Model with Applications - Li Cai VOLUME THREE: RESEARCH DESIGN AND SAMPLING Statistical Power of Abnormal-Social Psychological-Research - A Review - Jacob Cohen Do Studies of Statistical Power Have an Effect on the Power of Studies? - Peter Sedlmeier and Gerd Gigerenzer A Power Primer - Jacob Cohen Optimal Design in Psychological Research - Gary McClelland Statistical Analysis and Optimal Design for Cluster Randomized Trials - Stephen Raudenbush Analysis of a Trial Randomised in Clusters - Sally Kerry and J. Martin Bland The Design and Analysis of Longitudinal Studies of Development and Psychopathology in Context: Statistical Models and Methodological Recommendations - John Willett, Judith Singer and Nina Martin Missing Data: Our View of the State of the Art - Joseph Schafer and John Graham Propensity Score Estimation with Boosted Regression for Evaluating Causal Effects in Observational Studies - Daniel McCaffrey, Greg Ridgeway and Andrew Morral The Persistence of Underpowered Studies in Psychological Research: Causes, Consequences, and Remedies - Scott Maxwell VOLUME FOUR: STATISTICAL TESTS The Scree Test for the Number of Factors - Raymond Cattell Graphs in Statistical Analysis - F.J. Anscombe Primary, Secondary, and Meta-Analysis of Research - Gene Glass The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic and Statistical Considerations - Reuben Baron and David Kenny Thirteen Ways to Look at the Correlation Coefficient - Joseph Lee Rodgers and Alan Nicewander Why Covariance: A Rationale for Using Analysis of Covariance Procedures in Randomised Studies - Matthew Taylor and Mark Innocenti Factor Analysis in the Development and Refinement of Clinical Assessment Instruments - Frank Floyd and Keith Widaman Fixed-and Random-Effects Models in Meta-Analysis - Larry Hedges and Jack Vevea How Many Discoveries Have Been Lost by Ignoring Modern Statistical Methods? - Rand Wilcox A Comparison of Methods to Test Mediation and Other Intervening Variable Effects - David MacKinnon et al. Probing Interactions in Fixed and Multilevel Regression: Inferential and Graphical Techniques - Daniel Bauer and Patrick Curran Discrete Time Survival Mixture Analysis - Bengt Muthen and Katherine Masyn A Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables - Michael Smithson and Jay Verkuilen Average Causal Effects from Nonrandomized Studies - Joseph Schafer and Joseph Kang VOLUME FIVE: COMPLEX MODELS Significance Tests and Goodness of Fit in the Analysis of Covariance Structures - P. Bentler and Douglas Bonett The Dimensionality of Tests and Items - Roderick McDonald Asymptotically Distribution-Free Methods for the Analysis of Covariance Structures - M. Browne Model Selection and Akaike's Information Criterion (AIC): The General Theory and Its Analytical Extensions - Hamparsum Bozdogan Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach - James Anderson and David Gerbing Comparative Fit Indexes in Structural Models - P. Bentler Model Selection in Covariance Structures Analysis and the "Problem" of Sample Size: A Clarification - Robert Cudeck and Susan Henly Bootstrapping Goodness-of-Fit Measures in Structural Equation Models - Kenneth Bollen and Robert Stine Modeling Incomplete Longitudinal and Cross-Sectional Data Using Latent Growth Structural Models - J. McArdle and Fumiaki Hamagami Growth Curve Analysis in Accelerated Longitudinal Designs - Stephen Raudenbush and Wing-Shing Chan Distinguishing between Moderator and Quadratic Effects in Multiple Regression - Robert MacCallum and Corinne Mar The Robustness of Test Statistics to Nonnormality and Specification Error in Confirmatory Factor Analysis - Patrick Curran, Stephen West and John Finch Cutoff Criteria for Fit Indices in Covariance Structure Analysis: Conventional Criteria versus New Alternatives - Li-tze Hu and Peter Bentler On Sensitivity of Structural Equation Modeling to Latent Relation Misspecifications - Tenko Raykov To Parcel or Not to Parcel: Exploring the Question, Weighing the Merits - Todd Little et al. Distributional Assumptions of Growth Mixture Models: Implications for Overextraction of Latent Trajectory Classes - Daniel Bauer and Patrick Curran Autoregressive Latent Trajectory (ALT) Models: A Synthesis of Two Traditions - Keneth Bollen and Patrick Curran In Search of Golden Rules: Comment on Hypothesis-Testing Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu and Bentler's (1999) Findings - Herbert Marsh, Kit-Tai Hau and Zhonglin Wen Sufficient Sample Sizes for Multilevel Modeling - Cora Maas and Joop Hox An Empirical Evaluation of the Use of Fixed Cutoff Points in RMSEA Test Statistic in Structural Equation Models - Feinian Chen et al.

Product Details

  • ISBN13: 9781446282670
  • Format: Hardback
  • Number Of Pages: 1912
  • ID: 9781446282670
  • weight: 3630
  • ISBN10: 1446282678

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