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Psychometric Methods
Grounded in current knowledge and professional practice, this book provides up-to-date coverage of psychometric theory, methods, and interpretation of results. Essential topics include measurement and statistical concepts, scaling models, test design and development, reliability, validity, factor analysis, item response theory, and generalizability theory. Also addressed are norming and test equating, topics not typically covered in traditional psychometrics texts. Examples drawn from a dataset on intelligence testing are used throughout the book, elucidating the assumptions underlying particular methods and providing SPSS (or alternative) syntax for conducting analyses. The companion website presents datasets for all examples as well as PowerPoint slides of figures and key concepts. Pedagogical features include equation boxes with explanations of statistical notation, and end-of-chapter glossaries. The Appendix offers extensions of the topical chapters with example source code from SAS, SPSS, IRTPRO, BILOG-MG, PARSCALE, TESTFACT, and DIMTEST.
Clinical Interpretation of the WAIS-III and WMS-III
This guide to the WAIS-III and WMS-III tests is written to help clinical practitioners achieve efficient and accurate interpretations of test results. The only interpretive guide to be based on data obtained while standardizing the tests, this reference source provides new models for interpreting results, as well as practical information on the diagnostic validity, demographically corrected norms, and accuracy of the tests in measuring intelligence and memory. The focus of information is to allow clinicians to reduce variance in the interpretations of scores, indicating how best to factor in socio-economic status of respondents, interpreting meaningful change in serial assessments, and scori...
Longitudinal Structural Equation Modeling with Mplus
An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent state–trait (LST) theory as a unifying conceptual framework, including the relevant coefficients of consistency, occasion specificity, and reliability. Following a standard format, chapters review the theoretical underpinnings, strengths, and limitations of the various models; present data examples; and demonstrate each model's application and interpretation in Mplus, with numerous screen shots and output excerpts. Coverage encompasses both traditional models (autoregressive, change score, and growth curve models) and LST models for analyzing single- and multiple-indicator data. The book discusses measurement equivalence testing, intensive longitudinal data modeling, and missing data handling, and provides strategies for model selection and reporting of results. User-friendly features include special-topic boxes, chapter summaries, and suggestions for further reading. The companion website features data sets, annotated syntax files, and output for all of the examples.
Artificial Intelligence and Mental Health Care
New developments in machine learning (ML) and artificial intelligence (AI) hold great promise to revolutionize mental health care. In this context, ML and AI have been deployed for several different goals, including 1) the early detection of mental disorders, 2) the optimization of personalized treatments based on the individual characteristics of patients, 3) the better characterization of disorders detrimental to mental well-being and quality of life, as well as a better description of projected trajectories over time, and 4) the development of new treatments for mental health care. Despite their great potential to transform mental health care and occasional breakthroughs, ML and AI have n...
The Oxford Handbook of Quantitative Methods in Psychology: Vol. 2
The Oxford Handbook of Quantitative Methods in Psychology provides an accessible and comprehensive review of the current state-of-the-science and a one-stop source for learning and reviewing current best-practices in a quantitative methods across the social, behavioral, and educational sciences.
Measurement Theory and Applications for the Social Sciences
Which types of validity evidence should be considered when determining whether a scale is appropriate for a given measurement situation? What about reliability evidence? Using clear explanations illustrated by examples from across the social and behavioral sciences, this engaging text prepares students to make effective decisions about the selection, administration, scoring, interpretation, and development of measurement instruments. Coverage includes the essential measurement topics of scale development, item writing and analysis, and reliability and validity, as well as more advanced topics such as exploratory and confirmatory factor analysis, item response theory, diagnostic classification models, test bias and fairness, standard setting, and equating. End-of-chapter exercises (with answers) emphasize both computations and conceptual understanding to encourage readers to think critically about the material. ÿ
The Theory and Practice of Item Response Theory
Introduction to measurement -- The one-parameter model -- Joint maximum likelihood parameter estimation -- Marginal maximum likelihood parameter estimation -- The two-parameter model -- The three-parameter model -- Rasch models for ordered polytomous data -- Non-Rasch models for ordered polytomous data -- Models for nominal polytomous data -- Models for multidimensional data -- Linking and equating -- Differential item functioning -- Multilevel IRT models.
Conducting Personal Network Research
Written at an introductory level, and featuring engaging case examples, this book reviews the theory and practice of personal and egocentric network research. This approach offers powerful tools for capturing the impact of overlapping, changing social relationships and contexts on individuals' attitudes and behavior. The authors provide solid guidance on the formulation of research questions; research design; data collection, including decisions about survey modes and sampling frames; the measurement of network composition and structure, including the use of name generators; and statistical modeling, from basic regression techniques to more advanced multilevel and dynamic models. Ethical issues in personal network research are addressed. User-friendly features include boxes on major published studies, end-of-chapter suggestions for further reading, and an appendix describing the main software programs used in the field.
Regression Analysis and Linear Models
Ephasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion websi...
