The SAGE handbook of quantitative methodology for the social sciences /

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Quantitative methodology is a highly specialized field. This handbook is intended to introduce applied statisticians, empirical researchers & graduate students to the broad array of state-of-the-art quantitative methodologies in the social sciences.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Kaplan, David, 1955- (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Thousand Oaks, Calif. ; London : SAGE, 2004.
Temas:
Social sciences > Research > Methodology.
Social sciences > Statistical methods.
Social sciences > Mathematical models.
Sciences sociales > Recherche > Méthodologie.
Sciences sociales > Modèles mathématiques.
Sciences sociales > Méthodes statistiques.
REFERENCE > Questions & Answers.
Social sciences > Mathematical models
Social sciences > Research > Methodology
Social sciences > Statistical methods
Empirische Sozialforschung
Quantitative Methode
Sociaal-wetenschappelijk onderzoek.
Kwantitatieve methoden.
Sciences sociales.
Méthode quantitative.
Modèle mathématique.
Méthodologie de recherche.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Section I. Scaling
  • Dual Scaling / Shizuhiko Nishisato
  • Multidimensional Scaling and Unfolding of Symmetric and Asymmetric Proximity Relations / Willem J. Heiser and Frank M.T.A. Busing
  • Principal Components Analysis with Nonlinear Optimal Scaling Transformations for Ordinal and Nominal Data / Jacqueline J. Meulman, Anita J. Van der Kooij, and Willem J. Heiser
  • Section II. Testing and Measurement
  • Responsible Modeling of Measurement Data For Appropriate Inferences : Important Advances in Reliability and Validity Theory / Bruno D. Zumbo & André A. Rupp
  • Test Modeling / Ratna Nandakumar and Terry Ackerman
  • Differential Item Functioning Analysis : Detecting DIF Items and Testing DIF Hypotheses / Louis A. Roussos and William Stout
  • Understanding Computerized Adaptive Testing : From Robbins-Monro to Lord, and Beyond / Hua-Hua Chang
  • Section III. Models for Categorical Data
  • Trends in Categorical Data Analysis : New, Semi-new, and Recycled Ideas / David Rindskopf
  • Ordinal Regression Models / Valen E. Johnson and James H. Albert
  • Latent Class Models / Jay Magidson and Jeroen K. Vermunt
  • Discrete-Time Survival Analysis / John B. Willett and Judith D. Singer
  • Section IV. Models For Multilevel Data
  • An Introduction to Growth Modeling / Donald Hedeker
  • Multilevel Models for School Effectiveness Research / Russell W. Rumberger and Gregory J. Palardy
  • The Use of Hierarchical Models in Analyzing Data From Experiments and Quasi-Experiments Conducted in Field Settings / Michael Seltzer
  • Meta-analysis / Spyros Konstantopoulos and Larry V. Hedges
  • Section V. Models For Latent Variables
  • Determining the Number of Factors in Exploratory and Confirmatory Factor Analysis / Rick H. Hoyle and Jamieson L. Duvall
  • Experimental, Quasi-Experimental, and Nonexperimental design and Analysis with Latent Variables / Gregory R. Hancock
  • Applying Dynamic Factor Analysis in Behavioral and Social Science Research / John R. Nesselroade and Peter C.M. Molenaar
  • Latent Variable Analysis : Growth Mixture Modeling and Related Techniques For Longitudinal Data / Bengt Muthén
  • Section VI. Foundational Issues
  • Probabilistic Modeling with Bayesian Networks / Richard E. Neapolitan and Scott Morris
  • The Null Ritual : What You Always Wanted to Know About Significance Testing but Were Afraid to Ask / Gerd Gigerenzer, Stefan Krauss, and Oliver Vitouch
  • On Exogeneity / David Kaplan
  • Objectivity in Science and Structural Equation Modeling / Stanley A. Mulaik
  • Causal Inference / Peter Spirtes [and others].

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