The Sage handbook of quantitative methodology for the social sciences
By: David Kaplan, editor.
Contributors: Kaplan, David, 1955-; Sage Publications, inc.
Publisher: Sage
Published: 2004
Place of publication: Thousand Oaks, Calif
Language: eng
Number of pages: 511
Subjects: Social sciences -- Research -- Methodology.; Social sciences -- Mathematical models.
Description: 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.
Notes: Includes bibliographical references and indexes.
Table of contents: title: Dual scaling; title: Multidimensional scaling and unfolding of symmetric and asymmetric proximity relations; title: Principal components analysis with nonlinear optimal scaling transformations for ordinal and nominal data; title: Responsible modeling of measurement data for appropriate inferences : important advances in reliability and validity theory; title: Test modeling; title: Differential item functioning analysis : detecting DIF items and testing DIF hypotheses; title: Understanding computerized adaptive testing : from Robbins-Monro to Lord and beyond; title: Trends in categorical data analysis : new, semi-new, and recycled ideas; title: Ordinal regression models; title: Latent class models; title: Discrete-time survival analysis; title: An introduction to growth modeling; title: Multilevel models for school effectiveness research; title: The use of hierarchical models in analyzing data from experiments and quasi-experiments conducted in field settings; title: Meta-analysis; title: Determining the number of factors in exploratory and confirmatory factor analysis; title: Experimental, quasi-experimental, and nonexperimental design and analysis with latent variables; title: Applying dynamic factor analysis in behavioral and social science research; title: Latent variable analysis : growth mixture modeling and related techniques for longitudinal data; title: Probabilistic modeling with Bayesian networks; title: The null ritual : what you always wanted to know about significance testing but were afraid to ask; title: On exogeneity; title: Objectivity in science and structural equation modeling; title: Causal inference.