a paul meehl reader essays on the practice of scientific psychology multivariate applications series

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A Paul Meehl Reader

Author : Niels G. Waller
ISBN : 9781134812219
Genre : Psychology
File Size : 61. 50 MB
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This new book introduces a new generation to the important insights of Paul Meehl. In addition to selected papers from the classic reader, Psychodiagnosis, this book features new material selected from Meehl's most influential writings. The resulting collection is a tour de force illustrating quantitative analysis of life science problems, an examination of the inadequacy of some methods of analysis, and a review of the application of taxometrics. A Paul Meehl Reader is organized into five content areas: theory building and appraisal - how we discover and test the true causal relations of psychological constructs; specific etiology - an examination of genetic, behavioral, and environmental etiology in psychopathology; diagnosis and prediction - a review of the appropriate use of base rates; taxometrics - a look at Meehl's development of the method he invented; thinking effectively about psychological questions - a critique of correlation research and the power of quantitative thinking in psychology. The Reader features section introductions to orient the reader and provide a context and structure for Paul Meehl's work. The section on diagnosis and prediction features problem sets with solutions to guide the reader through practical applications of the principles described. An accompanying DVD contains footage from Paul Meehl's engaging seminar on clinical versus statistical prediction. This book appeals to advanced students and professionals in psychology, sociology, law, education, human development, and philosophy.

The Essence Of Multivariate Thinking

Author : Lisa L. Harlow
ISBN : 9781317859796
Genre : Education
File Size : 62. 55 MB
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By focusing on underlying themes, this book helps readers better understand the connections between multivariate methods. For each method the author highlights: the similarities and differences between the methods, when they are used and the questions they address, the key assumptions and equations, and how to interpret the results. The concepts take center stage while formulas are kept to a minimum. Examples using the same data set give readers continuity so they can more easily apply the concepts. Each method is also accompanied by a worked out example, SPSS and SAS input, and an example of how to write up the results. EQS code is used for the book’s SEM applications. This extensively revised edition features: New SEM chapters including an introduction (ch.10), path analysis (ch.11), confirmatory factor analysis (ch.12), and latent variable modeling (ch.13) the last three with an EQS application. A new chapter on multilevel modeling (ch. 8) that is now used more frequently in the social sciences. More emphasis on significance tests, effect sizes, and confidence intervals to encourage readers to adopt a thorough approach to assessing the magnitude of their findings. A new data set that explores the work environment. More discussion about the basic assumptions and equations for each method for a more accessible approach. New examples that help clarify the distinctions between methods. A new website at https://sites.google.com/site/multivariatesecondedition/ that features the datasets for all of the examples in the book for use in both SPSS and SAS and in EQS for the SEM chapters. The first two chapters review the core themes that run through most multivariate methods. The author shows how understanding multivariate methods is much more achievable when we notice the themes that underlie these statistical techniques. This multiple level approach also provides greater reliability and validity in our research. After providing insight into the core themes, the author illustrates them as they apply to the most popular multivariate methods used in the social, and behavioral sciences. First, two intermediate methods are explored – multiple regression and analysis of covariance. Next the multivariate grouping variable methods of multivariate analysis of variance, discriminant function analysis, and logistic regression are explored. Next the themes are applied to multivariate modeling methods including multilevel modeling, path analysis, confirmatory factor analysis, and latent variable models that include exploratory structural methods of principal component and factor analysis. The book concludes with a summary of the common themes and how they pertain to each method discussed in this book. Intended for advanced undergraduate and/or graduate courses in multivariate statistics taught in psychology, education, human development, business, nursing, and other social and life sciences, researchers also appreciate this book‘s applied approach. Knowledge of basic statistics, research methods, basic algebra, and finite mathematics is recommended.

Longitudinal Analysis

Author : Lesa Hoffman
ISBN : 9781317591092
Genre : Psychology
File Size : 44. 74 MB
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Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter. Written for non-mathematically-oriented readers, this text features: A description of the data manipulation steps required prior to model estimation so readers can more easily apply the steps to their own data An emphasis on how the terminology, interpretation, and estimation of familiar general linear models relates to those of more complex models for longitudinal data Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers’ understanding of the overall model-building process Sample results sections for each example to provide useful templates for published reports Examples using both real and simulated data in the text, along with syntax and output for SPSS, SAS, STATA, and Mplus at www.PilesOfVariance.com to help readers apply the models to their own data The book opens with the building blocks of longitudinal analysis—general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces unconditional longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. Conditional longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data. Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book’s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text.

Handbook Of Ethics In Quantitative Methodology

Author : Sonya K. Sterba
ISBN : 9781136888731
Genre : BUSINESS & ECONOMICS
File Size : 67. 28 MB
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"Part 1 presents ethical frameworks that cross-cut design, analysis, and modeling in the behavioral sciences. Part 2 focuses on ideas for disseminating ethical training in statistics courses. Part 3 considers the ethical aspects of selecting measurement instruments and sample size planning and explores issues related to high stakes testing, the defensibility of experimental vs. quasi-experimental research designs, and ethics in program evaluation. Decision points that shape a researchers' approach to data analysis are examined in Part 4 - when and why analysts need to account for how the sample was selected, how to evaluate tradeoffs of hypothesis-testing vs. estimation, and how to handle missing data. Ethical issues that arise when using techniques such as factor analysis or multilevel modeling and when making causal inferences are also explored. The book concludes with ethical aspects of reporting meta-analyses, of cross-disciplinary statistical reform, and of the publication process.

The Publishers Trade List Annual

Author :
ISBN : UOM:39015010965260
Genre : American literature
File Size : 21. 53 MB
Format : PDF
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Peri Psych S

Author : Aristotle
ISBN : OCLC:220741530
Genre : Philosophy, Ancient
File Size : 36. 94 MB
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