Description
SAGE PUBLISHING Quantitative Research In Psychology 5 Volumes Set 2014 Edition by Miles
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 powerVolume Two: MeasurementVolume Three: Research Design and samplingVolume Four: Statistical TestsVolume Five: Complex Models VOLUME ONE: STATISTICAL HYPOTHESIS TESTING AND POWERWhat Is Statistical Significance? - Ralph TylerBayesian Statistical Inference for Psychological Research - Ward Edwards, Harold Lindman and Leonard SavageStatistical Difficulties of Detecting Interactions and Moderator Effects - Gary McClelland and Charles JuddThe Earth Is Round (p < 0.05) - Jacob CohenPower Analysis and Determination of Sample Size for Covariance Structure Modeling - Robert MacCallum, Michael Browne and Hazuki SugawaraComputing Contrasts, Effect Sizes, and Counternulls on Other People's Published Data: General Procedures for Research Consumers - Ralph Rosnow and Robert RosenthalStatistical Significance Testing and Cumulative Knowledge in Psychology: Implications for the Training of Researchers - Frank SchmidtThe Appropriate Use of Null Hypothesis Significance Testing - Robert FrickControlling the Rate of Type I Error over a Large Set of Statistical Tests - H.J. Keselman, Robert Cribbie and Burt HollandHypothesis Testing and Theory Evaluation at the Boundaries: Surprising Insights from Bayes's Theorem - David TrafimowMindless Statistics - Gerd GigerenzerAn Alternative to Null-Hypothesis Significance Tests - Peter KilleenFalse-Positive Psychology Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant - Joseph Simmons, Leif Nelson and Uri SimonsohnVOLUME TWO: MEASUREMENTThe Proof and Measurement of Association between Two Things - C. SpearmanA Method of Scaling Psychological and Educational Tests - Louis ThurstoneMultiple Factor Analysis - Louis ThurstoneCoefficient Alpha and the Internal Structure of Tests - Lee CronbachThe Relation of Test Score to the Trait Underlying the Test - Frederic LordConstruct Validity in Psychological Tests - L. Cronbach and P. MeehlConvergent and Discriminant Validation by the Multitrait-Multimethod Matrix - Donald Campbell and Donald FiskeThe Axioms and Principal Results of Classical Test Theory - Melvin NovickA General Approach to Confirmatory Maximum Likelihood Factor Analysis - K. JoereskogIntraclass Correlations: Uses in Assessing Rater Reliability - Patrick Shrout and Joseph FleissMarginal Maximum Likelihood Estimation of Item Parameters: Application of an EM Algorithm - R. Darrell Bock and Murray AitkinA Taxonomy of Item Response Models - David Thissen and Lynne SteinbergThe New Rules of Measurement - Susan EmbretsonThe Concept of Validity - Denny Borsboom, Gideon Mellenbergh and Jaap van HeerdenOn the Use, the Misuse, and the Very Limited Usefulness of Cronbach's Alpha - Klaas SijtsmaA Two-Tier Full-Information Item Factor Analysis Model with Applications - Li CaiVOLUME THREE: RESEARCH DESIGN AND SAMPLINGStatistical Power of Abnormal-Social Psychological-Research - A Review - Jacob CohenDo Studies of Statistical Power Have an Effect on the Power of Studies? - Peter Sedlmeier and Gerd GigerenzerA Power Primer - Jacob CohenOptimal Design in Psychological Research - Gary McClellandStatistical Analysis and Optimal Design for Cluster Randomized Trials - Stephen RaudenbushAnalysis of a Trial Randomised in Clusters - Sally Kerry and J. Martin BlandThe Design and Analysis of Longitudinal Studies of Development and Psychopathology in Context: Statistical Models and Methodological Recommendations - John Willett, Judith Singer and Nina MartinMissing Data: Our View of the State of the Art - Joseph Schafer and John GrahamPropensity Score Estimation with Boosted Regression for Evaluating Causal Effects in Observational Studies - Daniel McCaffrey, Greg Ridgeway and Andrew MorralThe Persistence of Underpowered Studies in Psychological Research: Causes, Consequences, and Remedies - Scott MaxwellVOLUME FOUR: STATISTICAL TESTSThe Scree Test for the Number of Factors - Raymond CattellGraphs in Statistical Analysis - F.J. AnscombePrimary, Secondary, and Meta-Analysis of Research - Gene GlassThe Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic and Statistical Considerations - Reuben Baron and David KennyThirteen Ways to Look at the Correlation Coefficient - Joseph Lee Rodgers and Alan NicewanderWhy Covariance: A Rationale for Using Analysis of Covariance Procedures in Randomised Studies - Matthew Taylor and Mark InnocentiFactor Analysis in the Development and Refinement of Clinical Assessment Instruments - Frank Floyd and Keith WidamanFixed-and Random-Effects Models in Meta-Analysis - Larry Hedges and Jack VeveaHow Many Discoveries Have Been Lost by Ignoring Modern Statistical Methods? - Rand WilcoxA 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 CurranDiscrete Time Survival Mixture Analysis - Bengt Muthen and Katherine MasynA Better Lemon Squeezer? Maximum-Likelihood Regression with Beta-Distributed Dependent Variables - Michael Smithson and Jay VerkuilenAverage Causal Effects from Nonrandomized Studies - Joseph Schafer and Joseph KangVOLUME FIVE: COMPLEX MODELSSignificance Tests and Goodness of Fit in the Analysis of Covariance Structures - P. Bentler and Douglas BonettThe Dimensionality of Tests and Items - Roderick McDonaldAsymptotically Distribution-Free Methods for the Analysis of Covariance Structures - M. BrowneModel Selection and Akaike's Information Criterion (AIC): The General Theory and Its Analytical Extensions - Hamparsum BozdoganStructural Equation Modeling in Practice: A Review and Recommended Two-Step Approach - James Anderson and David GerbingComparative Fit Indexes in Structural Models - P. BentlerModel Selection in Covariance Structures Analysis and the "Problem" of Sample Size: A Clarification - Robert Cudeck and Susan HenlyBootstrapping Goodness-of-Fit Measures in Structural Equation Models - Kenneth Bollen and Robert StineModeling Incomplete Longitudinal and Cross-Sectional Data Using Latent Growth Structural Models - J. McArdle and Fumiaki HamagamiGrowth Curve Analysis in Accelerated Longitudinal Designs - Stephen Raudenbush and Wing-Shing ChanDistinguishing between Moderator and Quadratic Effects in Multiple Regression - Robert MacCallum and Corinne MarThe Robustness of Test Statistics to Nonnormality and Specification Error in Confirmatory Factor Analysis - Patrick Curran, Stephen West and John FinchCutoff Criteria for Fit Indices in Covariance Structure Analysis: Conventional Criteria versus New Alternatives - Li-tze Hu and Peter BentlerOn Sensitivity of Structural Equation Modeling to Latent Relation Misspecifications - Tenko RaykovTo 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 CurranAutoregressive Latent Trajectory (ALT) Models: A Synthesis of Two Traditions - Keneth Bollen and Patrick CurranIn 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 WenSufficient Sample Sizes for Multilevel Modeling - Cora Maas and Joop HoxAn Empirical Evaluation of the Use of Fixed Cutoff Points in RMSEA Test Statistic in Structural Equation Models - Feinian Chen et al.