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Measurement [Mental ] --- Measurement [Psychological ] --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychology--Measurement --- Psychology--Scaling --- Psychology--Statistics --- Psychometrics --- Psychometrie --- Psychometry (Psychophysics) --- Psychométrie --- Scaling [Psychological ] --- Psychologie --- Methodologie. --- Psychologie - Methodologie.

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"Preface Multilevel modeling has become a mainstream data analysis tool over the past decade, now figuring prominently in a range of social and behavioral science disciplines. Where it originally required specialized software, mainstream statistics packages such as IBM SPSS, SAS, and Stata all have included routines for multilevel modeling in their programs. Although some devotees of these statistical packages have been making good use of the relatively new multilevel modeling functionality, progress has been slower in carefully documenting these routines to facilitate meaningful access to the average user. Two years ago we developed Multilevel and Longitudinal Modeling with IBM SPSS to demonstrate how to use these techniques in IBM SPSS Version 18. Our focus was on developing a set of concepts and programming skills within the IBM SPSS environment that could be used to develop, specify, and test a variety of multilevel models with continuous outcomes, since IBM SPSS is a standard analytic tool used in many graduate programs and organizations globally. Our intent was to help readers gain facility in using the IBM SPSS linear-mixed models routine for continuous outcomes. We offered multiple examples of several different types of multilevel models, focusing on how to set up each model and how to interpret the output. At the time, mixed modeling for categorical outcomes was not available in the IBM SPSS software program. Over the past year or so, however, the generalized linear mixed model (GLMM) has been added to the mixed modeling analytic routine in IBM SPSS starting with Version 19. This addition prompted us to create this companion workbook that would focus on introducing readers to the multilevel approach to modeling with categorical outcomes"--

Quantitative methods in social research --- Psychometrics. --- Psychometrics --- Social sciences --- PSYCHOLOGY / Statistics. --- EDUCATION / Statistics. --- SOCIAL SCIENCE / Statistics. --- #SBIB:303H4 --- #SBIB:303H520 --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychology --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- Computer programs. --- Informatica in de sociale wetenschappen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Measurement --- Scaling --- Methodology --- SPSS (Computer file) --- SPSS for Windows. --- Statistical product and service solutions --- Statistical package for the social sciences --- SPSS (Computer file). --- EDUCATION / Statistics --- PSYCHOLOGY / Statistics --- SOCIAL SCIENCE / Statistics --- Computer programs

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"A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts. The author shows how to prepare a data set for import in Mplus using SPSS. He explains how to specify different types of models in Mplus syntax and address typical caveats--for example, assessing measurement invariance in longitudinal SEMs. Coverage includes path and factor analytic models as well as mediational, longitudinal, multilevel, and latent class models. Specific programming tips and solution strategies are presented in boxes in each chapter. The companion website features data sets, annotated syntax files, and output for all of the examples. Of special utility to instructors and students, many of the examples can be run with the free demo version of Mplus"--

Quantitative methods in social research --- Computer architecture. Operating systems --- Multivariate analysis --- #SBIB:303H4 --- #SBIB:303H520 --- Data processing. --- Informatica in de sociale wetenschappen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Mplus. --- Programming --- Data processing --- BUSINESS & ECONOMICS / Statistics. --- EDUCATION / Statistics. --- MEDICAL / Nursing / General. --- PSYCHOLOGY / Statistics. --- SOCIAL SCIENCE / Statistics.

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"Written in a friendly, conversational style, this book offers a hands-on approach to statistical mediation and moderation for both beginning researchers and those familiar with modeling. Starting with a gentle review of regression-based analysis, Paul Jose covers basic mediation and moderation techniques before moving on to advanced topics in multilevel modeling, structural equation modeling, and hybrid combinations, such as moderated mediation. User-friendly features include numerous graphs and carefully worked-through examples; "Helpful Suggestions" about procedures and pitfalls; "Knowledge Boxes" delving into special topics, such as dummy coding; and end-of-chapter exercises and problems (with answers). The companion website provides downloadable sample data sets that are used in the book to demonstrate particular analytic strategies, and explains how researchers and students can execute analyses using Jose's online programs, MedGraph and ModGraph. Appendices present SPSS, AMOS, and Mplus syntax for conducting the key types of analyses"-- "Written in a friendly, conversational style, this book offers a hands-on approach to statistical mediation and moderation for both beginning researchers and those familiar with modeling. Starting with a gentle review of regression-based analysis, Paul Jose covers basic mediation and moderation techniques before moving on to advanced topics in multilevel modeling, structural equation modeling, and hybrid combinations, such as moderated mediation. User-friendly features include numerous graphs and carefully worked-through examples; "Helpful Suggestions" about procedures and pitfalls; "Knowledge Boxes" delving into special topics, such as dummy coding; and end-of-chapter exercises and problems (with answers). The companion website provides downloadable sample data sets that are used in the book to demonstrate particular analytic strategies, and explains how researchers and students can execute analyses using Jose's online programs, MedGraph and ModGraph. Appendices present SPSS, AMOS, and Mplus syntax for conducting the key types of analyses. Keywords: data analysis, interaction effects, MedGraph, mediation, moderation, ModGraph, multilevel modeling, multivariate, quantitative methods, regression, research methodology, SEM, statistical techniques, structural equation modeling Audience: Applied researchers and graduate students in psychology, human development, education, sociology, public health, and management"--

Mediation (Statistics) --- Social sciences --- BUSINESS & ECONOMICS / Statistics --- EDUCATION / Statistics --- MEDICAL / Nursing / Research & Theory --- PSYCHOLOGY / Statistics --- #SBIB:303H510 --- Mediation analysis (Statistics) --- Mediational analysis (Statistics) --- Statistical mediation --- Statistical mediation analysis --- Regression analysis --- Statistical methods --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Quantitative methods in social research

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Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real data examples from a variety of disciplines, the significantly revised fourth edition incorporates recent developments such as Pearl's graphing theory and the structural causal model (SCM), measurement invariance, and more. Readers gain a comprehensive understanding of all phases of SEM, from data collection and screening to the interpretation and reporting of the results. Learning is enhanced by exercises with answers, rules to remember, and topic boxes. -- from back cover.

Structural equation modeling --- Social sciences --- 519.2 --- Statistical methods&delete& --- Data processing --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- SEM (Structural equation modeling) --- BUSINESS & ECONOMICS / Statistics. --- EDUCATION / Statistics. --- MEDICAL / Psychiatry / General. --- PSYCHOLOGY / Statistics. --- SOCIAL SCIENCE / Research. --- Structural equation modeling. --- Statistical methods --- Data processing. --- #SBIB:303H510 --- #SBIB:303H520 --- Civilization --- Multivariate analysis --- Factor analysis --- Regression analysis --- Path analysis (Statistics) --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Quantitative methods in social research --- Mathematical statistics --- Social sciences - Statistical methods - Data processing