Effect sizes for research : univariate and multivariate applications / / Robert J. Grissom and John J. Kim |
Autore | Grissom Robert J. |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | New York : , : Routledge, , 2012 |
Descrizione fisica | 1 online resource (453 p.) |
Disciplina | 519.5/38 |
Altri autori (Persone) | KimJohn J |
Soggetto topico |
Analysis of variance
Effect sizes (Statistics) Experimental design |
ISBN |
1-136-63234-4
1-136-63235-2 0-203-80323-X |
Classificazione | PSY032000EDU027000SOC027000 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Effect Sizes for Research Univariate and Multivariate Applications; Copyright; Contents; Preface; Acknowledgments; Chapter 1 Introduction; Introduction.; Null-Hypothesis Significance Testing; Statistically Signifying and Practical Significance.; Definition,Characteristics,and Uses of Effect Sizes; Some Factors Influencing Effect Sizes; Controversy About Null-Hypothesis Significance Testing; Purpose of This Book; Power Analysis; Replication and Meta-Analysis; Assumptions of Test Statistics and EffectSizes; Violations of Assumptions Suggested by Real Data
Yuen's Confidence Interval for the Difference Between Two Trimmed MeansOther Methods for Independent Groups; Criteria for Methods for Constructing a Confidence Interval; Dependent Groups; Summary; Questions; Chapter 3 The Standardized Difference Between Means; Introduction; Standardized Difference Between Treatment and Comparison Means Assuming Normality; Uses and Limitations of a Standardized Difference; Equal or Unequal Variances; Outliers and Standardized-Difference Effect Sizes; Tentative Recommendations; Additional Standardized-Difference Effect Sizes. Confidence Intervals for Standardized-Difference Effect SizesCounternull Effect Size.; Extreme Groups; Percent of Maximum Possible Score; Dependent Groups.; Effect Sizes for Pretest-Posttest Control-Group Designs; Summary; Questions.; Chapter 4 Correlational Effect Sizes and Related Topics; Introduction; Dichotomizing and Correlation; Point-Biserial Correlation; Unequal Base Rates in Nonexperimental Research; Correcting for Bias; Confidence Intervals for r pop; Null-Counternull Interval for r pop; Assumptions of Correlation and Point-Biserial Correlation Unequal Sample Sizes in Experimental ResearchUnreliability; Adjusting Effect Sizes for Unreliability; Restricted Range; Scale Coarseness; Small,Medium,and Large Effect Size Values; Binomial Effect Size Display; Coefficient of Determination.; Criticisms of the Coefficient of Determination; Slopes as Effect Sizes; Effect Sizes for Mediating and Moderating Variables; Summary; Questions; Chapter 5 Effect Size Measures That Go Beyond Comparing Two Averages; Introduction.; Probability of Superiority:Independent Groups.; Introduction to Overlap and Related Measures; Dominance Measure Cohen's Measures of Nonoverlap. |
Record Nr. | UNINA-9910779041203321 |
Grissom Robert J.
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New York : , : Routledge, , 2012 | ||
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Lo trovi qui: Univ. Federico II | ||
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Structural Equation Modeling with Mplus / / Byrne, Barbara |
Autore | Byrne Barbara |
Edizione | [1st edition] |
Pubbl/distr/stampa | Routledge, , 2013 |
Descrizione fisica | 1 online resource (431 p.) |
Disciplina | 519.5/3 |
Collana | Multivariate applications series |
Soggetto topico |
Structural equation modeling
Multivariate analysis Social sciences - Statistical methods |
ISBN |
1-136-66345-2
1-299-69326-1 1-136-66346-0 0-203-80764-2 |
Classificazione | PSY032000EDU027000SOC027000 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Structural Equation Modeling with Mplus Basic Concepts, Applications, and Programming; Copyright; Contents; Preface; Acknowledgments; Section I: Introduction; Chapter 1 Structural Equation Models: The Basics; Basic Concepts; The General Structural Equation Model; The General Mplus Structural Equation Model; Notes; Chapter 2 Using the Mplus Program; Mplus Notation and Input File Components and Structure; The Mplus Language Generator; Model Specification From Two Perspectives; The Concept of Model Identification; Overview of Remaining Chapters; Notes; Section II: Single-Group Analyses
Chapter 3 Testing the Factorial Validity of a Theoretical Construct: First-Order Confirmatory Factor Analysis ModelThe Hypothesized Model; Mplus Input File Specification and Output File Results; Hypothesis 2: Self-Concept Is a Two-Factor Structure; Mplus Input File Specification and Output File Results; Hypothesis 3: Self-Concept Is a One-Factor Structure; Notes; Chapter 4 Testing the Factorial Validity of Scores From a Measuring Instrument: First-Order Confirmatory Factor Analysis Model; The Measuring Instrument Under Study; The Hypothesized Model Mplus Input File Specification and Output File ResultsNotes; Addendum; Chapter 5 Testing the Factorial Validity of Scores From a Measuring Instrument: Second-Order Confirmatory Factor Analysis Model; The Hypothesized Model; Analysis of Categorical Data; Mplus Input File Specification and Output File Results; Notes; Chapter 6 Testing the Validity of a Causal Structure: Full Structural Equation Model; The Hypothesized Model; Mplus Input File Specification and Output File Results; Post Hoc Analyses; Notes; Section III: Multiple-Group Analyses Chapter 7 Testing the Factorial Equivalence of a Measuring Instrument: Analysis of Covariance StructuresTesting Multigroup Invariance: The General Notion; Testing Multigroup Invariance Across Independent Samples; The Hypothesized Model; Mplus Input File Specification and Output File Results; Notes; Chapter 8 Testing the Equivalence of Latent Factor Means: Analysis of Mean and Covariance Structures; Testing Latent Mean Structures: The Basic Notion; The Hypothesized Model; Testing Multigroup Invariance; Mplus Input File Specification and Output File Results Testing Multigroup Invariance: Other ConsiderationsNotes; Chapter 9 Testing the Equivalence of a Causal Structure: Full Structural Equation Model; Cross-Validation in Structural Equation Modeling; Testing Invariance Across Calibration and Validation Samples; The Hypothesized Model; Mplus Input File Specification and Output File Results; Notes; Section IV: Other Important Topics; Chapter 10 Testing Evidence of Construct Validity: The Multitrait-Multimethod Model; The General CFA Approach to MTMM Analyses; The Hypothesized Model; Mplus Input File Specification and Output File Results Examining Evidence of Construct Validity at the Matrix Level |
Record Nr. | UNINA-9910779026303321 |
Byrne Barbara
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Routledge, , 2013 | ||
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Lo trovi qui: Univ. Federico II | ||
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