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Informationen zum Autor Klappentext Robert DeVellis demystifies measurement by relating it to familiar experiences and by emphasizing a conceptual rather than a strictly mathematical understanding. Students' attention is drawn to important concepts that are foundational for subsequent topics, with opportunities provided to test understanding through chapter summaries and exercises. The Fourth Edition includes more attention to content validity and its relationship to scale breadth; a more thorough examination of coefficient alpha's limitations and remedies; discussion of "big measurement" vs "small measurement"; and additional discussion of the bifactor model in the chapter on factor analysis.This book presents complex concepts in a way that helps students to understand the logic underlying the creation, use, and evaluation of measurement instruments, and to develop a more intuitive feel for how scales work. Inhaltsverzeichnis 1. Overview General Perspectives on Measurement Historical Origins of Measurement in Social Science Later Developments in Measurement The Role of Measurement in the Social Sciences Summary and Preview Exercises 2. Understanding the Latent Variable Constructs versus Measures Latent Variable as the Presumed Cause of Item Values Path Diagrams Further Elaboration of the Measurement Model Parallel Tests Alternative Models Exercises Note 3. Reliability Methods Based on the Analysis of Variance Continuous versus Dichotomous Items Internal Consistency Reliability Based on Correlations Between Scale Scores Reliability and Statistical Power Generalizability Theory Summary Exercises Notes 4. Validity Content Validity Criterion-Related Validity Construct Validity Exercises 5. Guidelines in Scale Development Step 1: Determine Clearly What it is You Want to Measure Step 2: Generate an Item Pool Step 3: Determine the Format for Measurement Step 4: Have Initial Item Pool Reviewed by Experts Step 5: Consider Inclusion of Validation Items Step 6: Administer Items to a Development Sample Step 7: Evaluate the Items Step 8: Optimize Scale Length Exercises Note 6. Factor Analysis Overview of Factor Analysis Conceptual Description of Factor Analysis Bifactor and Hierarchical Factor Models Interpreting Factors Principle Components versus Common Factors Confirmatory Factor Analysis Using Factor Analysis in Scale Development Sample Size Conclusion Exercises 7. An Overview of Item Response Theory Item Difficulty Item Discrimination Guessing, or False Positives Item-Characteristic Curves IRT Applied to Multiresponse Items Conclusions Exercises 8. Measurement in the Broader Research Context Before Scale Development After Scale Administration Final Thoughts Exercises ...
