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The SAGE handbook of quantitative methodology for the social sciences /

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:
Acceso en línea:Texto completo

MARC

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245 0 4 |a The SAGE handbook of quantitative methodology for the social sciences /  |c David Kaplan, editor. 
246 1 |i Available from some providers with title:  |a Sage research methods online 
246 3 0 |a Quantitative methodology for the social sciences 
260 |a Thousand Oaks, Calif. ;  |a London :  |b SAGE,  |c 2004. 
300 |a 1 online resource (xiii, 511 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file 
504 |a Includes bibliographical references and index. 
520 8 |a 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. 
588 0 |a Print version record. 
505 0 0 |g Section I.  |t Scaling --  |t Dual Scaling /  |r Shizuhiko Nishisato --  |t Multidimensional Scaling and Unfolding of Symmetric and Asymmetric Proximity Relations /  |r Willem J. Heiser and Frank M.T.A. Busing --  |t Principal Components Analysis with Nonlinear Optimal Scaling Transformations for Ordinal and Nominal Data /  |r Jacqueline J. Meulman, Anita J. Van der Kooij, and Willem J. Heiser --  |g Section II.  |t Testing and Measurement --  |t Responsible Modeling of Measurement Data For Appropriate Inferences : Important Advances in Reliability and Validity Theory /  |r Bruno D. Zumbo & André A. Rupp --  |t Test Modeling /  |r Ratna Nandakumar and Terry Ackerman --  |t Differential Item Functioning Analysis : Detecting DIF Items and Testing DIF Hypotheses /  |r Louis A. Roussos and William Stout --  |t Understanding Computerized Adaptive Testing : From Robbins-Monro to Lord, and Beyond /  |r Hua-Hua Chang --  |g Section III.  |t Models for Categorical Data --  |t Trends in Categorical Data Analysis : New, Semi-new, and Recycled Ideas /  |r David Rindskopf --  |t Ordinal Regression Models /  |r Valen E. Johnson and James H. Albert --  |t Latent Class Models /  |r Jay Magidson and Jeroen K. Vermunt --  |t Discrete-Time Survival Analysis /  |r John B. Willett and Judith D. Singer --  |g Section IV.  |t Models For Multilevel Data --  |t An Introduction to Growth Modeling /  |r Donald Hedeker --  |t Multilevel Models for School Effectiveness Research /  |r Russell W. Rumberger and Gregory J. Palardy --  |t The Use of Hierarchical Models in Analyzing Data From Experiments and Quasi-Experiments Conducted in Field Settings /  |r Michael Seltzer --  |t Meta-analysis /  |r Spyros Konstantopoulos and Larry V. Hedges --  |g Section V.  |t Models For Latent Variables --  |t Determining the Number of Factors in Exploratory and Confirmatory Factor Analysis /  |r Rick H. Hoyle and Jamieson L. Duvall --  |t Experimental, Quasi-Experimental, and Nonexperimental design and Analysis with Latent Variables /  |r Gregory R. Hancock --  |t Applying Dynamic Factor Analysis in Behavioral and Social Science Research /  |r John R. Nesselroade and Peter C.M. Molenaar --  |t Latent Variable Analysis : Growth Mixture Modeling and Related Techniques For Longitudinal Data /  |r Bengt Muthén --  |g Section VI.  |t Foundational Issues --  |t Probabilistic Modeling with Bayesian Networks /  |r Richard E. Neapolitan and Scott Morris --  |t The Null Ritual : What You Always Wanted to Know About Significance Testing but Were Afraid to Ask /  |r Gerd Gigerenzer, Stefan Krauss, and Oliver Vitouch --  |t On Exogeneity /  |r David Kaplan --  |t Objectivity in Science and Structural Equation Modeling /  |r Stanley A. Mulaik --  |t Causal Inference /  |r Peter Spirtes [and others]. 
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650 6 |a Sciences sociales  |x Modèles mathématiques. 
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650 7 |a Social sciences  |x Research  |x Methodology  |2 fast 
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