The British Journal of Mathematical & Statistical Psychology
Author :
Publisher :
Page : 384 pages
File Size : 25,10 MB
Release : 1993
Category : Psychology
ISBN :
Author :
Publisher :
Page : 384 pages
File Size : 25,10 MB
Release : 1993
Category : Psychology
ISBN :
Author : David Clark-Carter
Publisher : Routledge
Page : 718 pages
File Size : 31,14 MB
Release : 2018-12-07
Category : Psychology
ISBN : 1315398133
Quantitative Psychological Research: The Complete Student's Companion expertly guides the reader through all the stages involved in undertaking quantitative psychological research: designing a study, choosing a sample of people, undertaking the study, analysing the data, and reporting the research. Accessibly written and clearly presented, the book is designed for anyone learning to conduct quantitative psychological research. It covers the full research process, from the original idea to reporting the completed study, emphasising the importance of looking beyond statistical significance in evaluating data. The book provides step-by-step guidance on choosing, interpreting and reporting the appropriate analysis, featuring worked examples and extended calculations as appendices for advanced readers. This edition features new chapters on exploratory factor analysis, logistic regression and Bayesian statistics, and has been thoroughly updated throughout to reflect the latest research practices. Care has been taken to avoid tying the book to any specific statistical software, providing readers with a thorough grounding in the basics no matter which package they go on to use. Whether you’re at the beginning of your undergraduate degree or working towards your masters or doctorate, this book will be invaluable for anyone looking to understand how to conduct quantitative psychological research.
Author : Albert Maydeu-Olivares
Publisher : Psychology Press
Page : 596 pages
File Size : 48,84 MB
Release : 2005-05-06
Category : Education
ISBN : 1135623163
Contemporary Psychometrics features cutting edge chapters organized in four sections: test theory, factor analysis, structural equation modeling, and multivariate analysis. The section on test theory includes topics such as multidimensional item response theory (IRT), the relationship between IRT and factor analysis, estimation and testing of these models, and basic measurement issues that are often neglected. The factor analysis section reviews the history and development of the model, factorial invariance and factor analysis indeterminacy, and Bayesian inference for factor scores and parameter estimates. The section on structural equation modeling (SEM) includes the general algebraic-graphic rules for latent variable SEM, a survey of goodness of fit assessment, SEM resampling methods, a discussion of how to compare correlations between and within independent samples, dynamic factor models based on ARMA time series models, and multi-level factor analysis models for continuous and discrete data. The final section on multivariate analysis includes topics such as dual scaling of ordinal data, model specification and missing data problems in time series models, and a discussion of the themes that run through all multivariate methods. This tour de force through contemporary psychometrics will appeal to advanced students and researchers in the social and behavioral sciences and education, as well as methodologists from other disciplines.
Author : David J. Bartholomew
Publisher : John Wiley & Sons
Page : 241 pages
File Size : 23,57 MB
Release : 2011-06-28
Category : Mathematics
ISBN : 1119973708
Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor analysis and latent variable modeling from a statistical perspective. This book presents a general framework to enable the derivation of the commonly used models, along with updated numerical examples. Nature and interpretation of a latent variable is also introduced along with related techniques for investigating dependency. This book: Provides a unified approach showing how such apparently diverse methods as Latent Class Analysis and Factor Analysis are actually members of the same family. Presents new material on ordered manifest variables, MCMC methods, non-linear models as well as a new chapter on related techniques for investigating dependency. Includes new sections on structural equation models (SEM) and Markov Chain Monte Carlo methods for parameter estimation, along with new illustrative examples. Looks at recent developments on goodness-of-fit test statistics and on non-linear models and models with mixed latent variables, both categorical and continuous. No prior acquaintance with latent variable modelling is pre-supposed but a broad understanding of statistical theory will make it easier to see the approach in its proper perspective. Applied statisticians, psychometricians, medical statisticians, biostatisticians, economists and social science researchers will benefit from this book.
Author : Debbie L. Hahs-Vaughn
Publisher : Routledge
Page : 782 pages
File Size : 20,61 MB
Release : 2020-01-17
Category : Psychology
ISBN : 1000124436
Statistical Concepts—A Second Course presents the last 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for second and upper-level statistics courses, this book highlights how statistics work and how best to utilize them to aid students in the analysis of their own data and the interpretation of research results. In this new edition, Hahs-Vaughn and Lomax discuss sensitivity, specificity, false positive and false negative errors. Coverage of effect sizes has been expanded upon and more organizational features (to summarize key concepts) have been included. A final chapter on mediation and moderation has been added for a more complete presentation of regression models. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R. This book acts as a clear and accessible instructional tool to help readers fully understand statistical concepts and how to apply them to data. It is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral science disciplines.
Author : Rand Wilcox
Publisher : CRC Press
Page : 862 pages
File Size : 28,98 MB
Release : 2011-08-05
Category : Mathematics
ISBN : 1439834563
In addition to learning how to apply classic statistical methods, students need to understand when these methods perform well, and when and why they can be highly unsatisfactory. Modern Statistics for the Social and Behavioral Sciences illustrates how to use R to apply both standard and modern methods to correct known problems with classic techniques. Numerous illustrations provide a conceptual basis for understanding why practical problems with classic methods were missed for so many years, and why modern techniques have practical value. Designed for a two-semester, introductory course for graduate students in the social sciences, this text introduces three major advances in the field: Early studies seemed to suggest that normality can be assumed with relatively small sample sizes due to the central limit theorem. However, crucial issues were missed. Vastly improved methods are now available for dealing with non-normality. The impact of outliers and heavy-tailed distributions on power and our ability to obtain an accurate assessment of how groups differ and variables are related is a practical concern when using standard techniques, regardless of how large the sample size might be. Methods for dealing with this insight are described. The deleterious effects of heteroscedasticity on conventional ANOVA and regression methods are much more serious than once thought. Effective techniques for dealing heteroscedasticity are described and illustrated. Requiring no prior training in statistics, Modern Statistics for the Social and Behavioral Sciences provides a graduate-level introduction to basic, routinely used statistical techniques relevant to the social and behavioral sciences. It describes and illustrates methods developed during the last half century that deal with known problems associated with classic techniques. Espousing the view that no single method is always best, it imparts a general understanding of the relative merits of various techniques so that the choice of method can be made in an informed manner.
Author : Stanley H. Cohen
Publisher : Psychology Press
Page : 207 pages
File Size : 31,89 MB
Release : 2019-10-25
Category : Psychology
ISBN : 1317739337
Dealing with the methodological and data analytic problems in developmental research, this book presents solutions advanced from the disciplinary perspectives of psychology, behavior analysis and behavioral systems, sociology, and anthropology. Topics addressed include: * the metatheoretical issues about the relationship between data and theory * the identification and analysis of age, cohort, and time-of-measurement effects * the assessment of quantitative and qualitative change * the use of group and single-subject designs for control by systematic variation * the use of systems methodology to investigate the developmental continuity and organization of behavior * the analysis of data from repeated measures designs * the use of structural equations and path analysis to test causal hypotheses * the use of structured relational matrices to study development and change This unique volume offers students an unusually wide range of research tools for identifying and studying specific developmental problems.
Author : Norman Cliff
Publisher : Psychology Press
Page : 212 pages
File Size : 11,94 MB
Release : 2014-03-05
Category : Psychology
ISBN : 1317781430
This book was written with the belief that ordinal statistical methods--sometimes discussed under the title of "nonparametric statistics"--deserve much more serious attention as research tools than they have traditionally had. There are three classes of reasons for this: *Many behavioral variables constitute only ordinal scales, not interval measurements that are required for traditional statistics. *Various research issues that are of primary interest in behavioral research are themselves questions about order: Which group scores higher? Is the order on this variable similar to the order on that? *Inferences from ordinal statistics are less subject to distributional peculiarities of the data than are those from traditional statistics. Taking an innovative approach, this book treats ordinal methods in an integrated way rather than as a compendium of unrelated methods, and emphasizes that the ordinal quantities are highly meaningful in their own right, not just as stand-ins for more traditional correlations or analyses of variance. In fact, since the ordinal statistics have desirable descriptive properties of their own, the book treats them parametrically, rather then nonparametrically. The author discusses how ordinal statistics can be applied in a much wider set of research situations than has usually been thought, and that they can often come closer to answering the researcher's primary questions than traditional ones can. And he includes some extensions of ordinal methods in order to accomplish that end.
Author : James P. Stevens
Publisher : Routledge
Page : 666 pages
File Size : 31,43 MB
Release : 2012-11-12
Category : Education
ISBN : 1136910697
This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.
Author : Rupert G. Jr. Miller
Publisher : Springer Science & Business Media
Page : 311 pages
File Size : 19,55 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 1461381223
Simultaneous Statistical Inference, which was published originally in 1966 by McGraw-Hill Book Company, went out of print in 1973. Since then, it has been available from University Microfilms International in xerox form. With this new edition Springer-Verlag has republished the original edition along with my review article on multiple comparisons from the December 1977 issue of the Journal of the American Statistical Association. This review article covered developments in the field from 1966 through 1976. A few minor typographical errors in the original edition have been corrected in this new edition. A new table of critical points for the studentized maximum modulus is included in this second edition as an addendum. The original edition included the table by K. C. S. Pillai and K. V. Ramachandran, which was meager but the best available at the time. This edition contains the table published in Biometrika in 1971 by G. 1. Hahn and R. W. Hendrickson, which is far more comprehensive and therefore more useful. The typing was ably handled by Wanda Edminster for the review article and Karola Decleve for the changes for the second edition. My wife, Barbara, again cheerfully assisted in the proofreading. Fred Leone kindly granted permission from the American Statistical Association to reproduce my review article. Also, Gerald Hahn, Richard Hendrickson, and, for Biometrika, David Cox graciously granted permission to reproduce the new table of the studentized maximum modulus. The work in preparing the review article was partially supported by NIH Grant ROI GM21215.