The Sage handbook of quantitative methodology for the social sciences
`This Handbook discusses important methodological tools and topics in quantitative methodology in easy to understand language. It is an exhaustive review of past and recent advances in each topic combined with a detailed discussion of examples and graphical illustrations. It will be an essential ref...
Saved in:
| Main Author: | |
|---|---|
| Format: | eBook Book |
| Language: | English |
| Published: |
Thousand Oaks, Calif
Sage
2004
SAGE Publications, Incorporated SAGE Publications, Inc Sage Publications |
| Edition: | 1 |
| Subjects: | |
| ISBN: | 9780761923596, 0761923594 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- Chapter 20 - Probabilistic Modeling With Bayesian Networks -- Chapter 21 - The Null Ritual: What You Always Wanted to Know About Significance Testing but Were Afraid to Ask -- Chapter 22 - On Exogeneity -- Chapter 23 - Objectivity in Science and Structural Equation Modeling -- Chapter 24 - Causal Inference -- Name Index -- Subject Index -- About the Editor
- Cover -- Contents -- Preface -- Acknowledgments -- Section I - Scaling -- Chapter 1 - Dual Scaling -- Chapter 2 - Multidimensional Scaling and Unfolding of Symmetric and Asymmetric Proximity Relations -- Chapter 3 - Principal Components Analysis With Nonlinear Optimal Scaling Transformations for Ordinal and Nominal Data -- Section II - Testing and Measurment -- Chapter 4 - Responsible Modeling of Measurement Data for Appropriate Inferences: Important Advances in Reliability and Validity Theory -- Chapter 5 - Test Modeling -- Chapter 6 - Differential Item Functioning Analysis: Detecting DIF Items and Testing DIF Hypotheses -- Chapter 7 - Understanding Computerized Adaptive Testing: From Robbins-Monro to Lord and Beyond -- Section III - Models for Categorical Data -- Chapter 8 - Trends in Categorical Data Analysis: New, Semi-New, and Recycled Ideas -- Chapter 9 - Ordinal Regression Models -- Chapter 10 - Latent Class Models -- Chapter 11 - Discrete-Time Survival Analysis -- Section IV - Models for Multilevel Data -- Chapter 12 - An Introduction to Growth Modeling -- Chapter 13 - Multilevel Models for School Effectiveness Research -- Chapter 14 - The Use of Hierarchical Models in Analyzing Data From Experiments and Quasi-Experiments Conducted in Field Settings -- Chapter 15 - Meta-Analysis: Spyros Konstantopoulos -- Section V - Models for Latent Variables -- Chapter 16 - Determining the Number of Factors in Exploratory and Confirmatory Factor Analysis -- Chapter 17 - Experimental, Quasi-Experimental, and Nonexperimental Design and Analysis With Latent Variables -- Chapter 18 - Applying Dynamic Factor Analysis in Behavioral and Social Science Research -- Chapter 19 - Latent Variable Analysis: Growth Mixture Modeling and Related Techniques for Longitudinal Data -- Section VI - Foundational Issues
- Dual Scaling -- Multidimensional Scaling and Unfolding of Symmetric and Asymmetric Proximity Relations -- Principal Components Analysis With Nonlinear Optimal Scaling Transformations for Ordinal and Nominal Data -- Responsible Modeling of Measurement Data for Appropriate Inferences: Important Advances in Reliability and Validity Theory -- Test Modeling -- Differential Item Functioning Analysis: Detecting DIF Items and Testing DIF Hypotheses -- Understanding Computerized Adaptive Testing: From Robbins-Monro to Lord and Beyond -- Trends in Categorical Data Analysis: New, Semi-New, and Recycled Ideas -- Ordinal Regression Models -- Latent Class Models -- Discrete-Time Survival Analysis -- An Introduction to Growth Modeling -- Multilevel Models for School Effectiveness Research -- The Use of Hierarchical Models in Analyzing Data From Experiments and Quasi-Experiments Conducted in Field Settings -- Meta-Analysis: Spyros Konstantopoulos -- Determining the Number of Factors in Exploratory and Confirmatory Factor Analysis -- Experimental, Quasi-Experimental, and Nonexperimental Design and Analysis With Latent Variables -- Applying Dynamic Factor Analysis in Behavioral and Social Science Research -- Latent Variable Analysis: Growth Mixture Modeling and Related Techniques for Longitudinal Data -- Probabilistic Modeling With Bayesian Networks -- The Null Ritual: What You Always Wanted to Know About Significance Testing but Were Afraid to Ask -- On Exogeneity -- Objectivity in Science and Structural Equation Modeling -- Causal Inference