Applied Analysis Of Variance In Behavioral Science
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Author | : Lynne Edwards |
Publisher | : CRC Press |
Total Pages | : 652 |
Release | : 1993-06-16 |
Genre | : Mathematics |
ISBN | : 9780824788964 |
A reference devoted to the discussion of analysis of variance (ANOVA) techniques. It presents ANOVA as a research design, a collection of statistical models, an analysis model, and an arithmetic summary of data. Discussion focuses primarily on univariate data, but multivariate generalizations are to
Author | : Jacob Cohen |
Publisher | : Routledge |
Total Pages | : 625 |
Release | : 2013-05-13 |
Genre | : Psychology |
ISBN | : 1134742770 |
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Author | : Christopher L. Aberson |
Publisher | : Routledge |
Total Pages | : 194 |
Release | : 2019-01-24 |
Genre | : Psychology |
ISBN | : 1351695061 |
Applied Power Analysis for the Behavioral Sciences is a practical "how-to" guide to conducting statistical power analyses for psychology and related fields. The book provides a guide to conducting analyses that is appropriate for researchers and students, including those with limited quantitative backgrounds. With practical use in mind, the text provides detailed coverage of topics such as how to estimate expected effect sizes and power analyses for complex designs. The topical coverage of the text, an applied approach, in-depth coverage of popular statistical procedures, and a focus on conducting analyses using R make the text a unique contribution to the power literature. To facilitate application and usability, the text includes ready-to-use R code developed for the text. An accompanying R package called pwr2ppl (available at https://github.com/chrisaberson/pwr2ppl) provides tools for conducting power analyses across each topic covered in the text.
Author | : Michael N. Mitchell |
Publisher | : |
Total Pages | : 0 |
Release | : 2015 |
Genre | : Psychology |
ISBN | : 9781597181730 |
Stata for the Behavioral Sciences, by Michael Mitchell, is the ideal reference for researchers using Stata to fit ANOVA models and other models commonly applied to behavioral science data. Drawing on his education in psychology and his experience in consulting, Mitchell uses terminology and examples familiar to he reader as he demonstrates how to fit a variety of models, how to interpret results, how to understand simple and interaction effects, and how to explore results graphically. Although this book is not designed as an introduction to Stata, it is appealing even to Stata novices. Throughout the text, Mitchell thoughtfully addresses any features of Stata that are important to understand for the analysis at hand. He also is careful to point out additional resources such as related videos from Stata's YouTube channel. This book is an easy-to-follow guide to analyzing data using Stata for researchers in the behavioral sciences and a valuable addition to the bookshelf of anyone interested in applying ANOVA methods to a variety of experimental designs.
Author | : Andrew Rutherford |
Publisher | : John Wiley & Sons |
Total Pages | : 358 |
Release | : 2012-08-29 |
Genre | : Mathematics |
ISBN | : 1118491696 |
Provides an in-depth treatment of ANOVA and ANCOVA techniques from a linear model perspective ANOVA and ANCOVA: A GLM Approach provides a contemporary look at the general linear model (GLM) approach to the analysis of variance (ANOVA) of one- and two-factor psychological experiments. With its organized and comprehensive presentation, the book successfully guides readers through conventional statistical concepts and how to interpret them in GLM terms, treating the main single- and multi-factor designs as they relate to ANOVA and ANCOVA. The book begins with a brief history of the separate development of ANOVA and regression analyses, and then goes on to demonstrate how both analyses are incorporated into the understanding of GLMs. This new edition now explains specific and multiple comparisons of experimental conditions before and after the Omnibus ANOVA, and describes the estimation of effect sizes and power analyses leading to the determination of appropriate sample sizes for experiments to be conducted. Topics that have been expanded upon and added include: Discussion of optimal experimental designs Different approaches to carrying out the simple effect analyses and pairwise comparisons with a focus on related and repeated measure analyses The issue of inflated Type 1 error due to multiple hypotheses testing Worked examples of Shaffer's R test, which accommodates logical relations amongst hypotheses ANOVA and ANCOVA: A GLM Approach, Second Edition is an excellent book for courses on linear modeling at the graduate level. It is also a suitable reference for researchers and practitioners in the fields of psychology and the biomedical and social sciences.
Author | : Scott E. Maxwell |
Publisher | : Psychology Press |
Total Pages | : 1106 |
Release | : 2004 |
Genre | : Analysis of variance |
ISBN | : 0805837183 |
CD-ROM contains: "SPSS and SAS data sets fpr ,amu pf tje text exercoses as we;; as titorials reviewing basic statistics and simple and multiple regression."
Author | : Howard E.A. Tinsley |
Publisher | : Academic Press |
Total Pages | : 751 |
Release | : 2000-05-22 |
Genre | : Mathematics |
ISBN | : 0080533566 |
Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.
Author | : Richard J. Harris |
Publisher | : Psychology Press |
Total Pages | : 635 |
Release | : 2001-05-01 |
Genre | : Psychology |
ISBN | : 1135555362 |
Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why one should consider diving into more detailed treatments of computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory factor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.
Author | : Hardeo Sahai |
Publisher | : Springer Science & Business Media |
Total Pages | : 766 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461213444 |
The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.
Author | : Lawrence S. Meyers |
Publisher | : SAGE |
Total Pages | : 768 |
Release | : 2006 |
Genre | : Mathematics |
ISBN | : 9781412904124 |
Multivariate designs were once the province of the very few exalted researchers who understood the underlying advanced mathematics. Today, through the sophistication of statistical software packages such as SPSS, virtually all graduate students across the social and behavioural sciences are exposed to the complex multivariate statistical techniques without having to learn the mathematical computations needed to acquire the data output. These students - in psychology, education, political science, etc. - will never be statisticians and appropriately so, their preparation and coursework reflects less of an emphasis on the mathematical complexities of multivariate statistics and more on the analysis and the interpretation of the methods themselves and the actual data output. This book provides full coverage of the wide range of multivariate topics in a conceptual, rather than mathematical, approach. The author gears toward the needs, level of sophistication, and interest in multivariate methodology of students in applied areas that need to focus on design and interpretation rather than the intricacies of specific computations. The book includes: - Coverage of the most widely used multivariate designs: multiple regression, exploratory factor analysis, MANOVA, and structural equation modeling. - Integrated SPSS examples for hands-on learning from one large study (for consistency of application throughout the text). - Examples of written results to enable students to learn how the results of these procedures are communicated. - Practical application of the techniques using contemporary studies that will resonate with students.