Intended for the social scientist who must develop a rating on attitudes, values and opinions, this text provides information on the construction of more effective scales. It includes information on how to validate a scale and how to develop a summated rating scale based on classical test theory.

This series of methodological works provides introductory explanations and demonstrations of various data analysis techniques applicable to the social sciences. Designed for readers with a limited background in statistics or mathematics, this series aims to make the assumptions and practices of quantitative analysis more readily accessible.

"This book is concerned with techniques for the construction of attitude scales. Once a set of attitude statements has been collected, there are two general methods that have been used in the development of attitude scales. One of these methods involves the use of a judging group. The judging group is not asked to respond to the statements in terms of their own agreement or disagreement with them, but rather to judge the degree of favorableness or unfavorableness expressed by each statement. These judgments are then used as a basis for determining scale values of the statements upon a psychological continuum. Once the scale values of the statements are known, subjects can then be asked to express their agreement or disagreement with the individual statements. Attitude scores for these subjects can then be obtained based upon the prior knowledge of the scale values of the statements. The judgment methods for constructing attitude scales differ only in the manner in which the judgments and scale values of the statements are obtained. They include the method of paired comparisons, the method of equal-appearing intervals, and the method of successive intervals. These methods are described in Chapters 2 through 5. A second method of developing attitude scales is based upon direct responses of agreement or disagreement with attitude statements. Since the response methods do not require prior knowledge of the scale values of the statements in any exact sense, a judging group is not necessary. It is sufficient for the response methods if one can assume that the response "agree" to a statement indicates a more favorable attitude than the response "disagree," or vice versa. The response methods for constructing attitude scales include the method of summated ratings and scalogram analysis. These methods are presented in Chapters 6 and 7. Another method for constructing an attitude scale that makes use of both judgments and responses is described in Chapter 8. This method is termed the scale-discrimination technique. It is an early effort upon the part of Kilpatrick and myself at a synthesis of a scaling and a response method for developing an attitude scale. H-technique, as described in Chapter 9, is also a response method. It has as its objective the improvement of a cumulative scale--a kind of scale about which more will be said in the text. In this chapter I have also described another effort at a synthesis of scaling and response methods which, for want of a better name, I have called W-technique. This, in brief, represents the content of this book"--Preface. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Author Paul E. Spector provides a clear introduction to the principles of experimental and non-experimental design, including single group design, pre-test, post-test designs, and factorial designs. Spector also covers hierarchical designs, multivariate designs, the Solomon four group design, panel designs, and designs with concomitant variables.

Distilling the vast literature on this most frequently studied variable in organizational behavior, Paul E. Spector provides students and professionals with a pithy overview of the research and application of job satisfaction. In addition to discussing the nature of and techniques for assessing job satisfaction, this text summarizes the findings regarding how people feel toward work, including cultural and gender differences in job satisfaction, personal and organizational antecedents, potential consequences, and interventions to improve job satisfaction. Students, researchers, and practitioners will particularly appreciate the extensive list of references and the Job Satisfaction Survey included in the Appendix. This book includes the latest research and new topics including the business case for job satisfaction, customer service, disabled workers, leadership, mental health, organizational climate, virtual work, and work-family issues. Further, paulspector.com features an ongoing series of blog articles, links to assessments mentioned in the book, and other resources on job satisfaction to coincide with this text. This book is ideal for professionals, researchers, and undergraduate and graduate students in industrial and organizational psychology and organizational behavior, as well as in specialized courses on job attitudes or job satisfaction. .

Effective measurement is a cornerstone of scientific research. Yet many social science researchers lack the tools to develop appropriate assessment instruments for the measurement of latent social-psychological constructs. Scaling Procedures for Self-Report Measures in the Social Sciences examines the issues involved in developing and validating multi-item self-report scales of latent constructs. Distinguished researchers and award-winning educators Richard G Netemeyer, William O Bearden, and Subhash Sharma present a four-step approach for multi-indicator scale development. With these steps, the authors include relevant empirical examples and a review of the concepts of dimensionality, reliability, and validity. Scaling Procedures: Issues and Applications supplies cutting-edge strategies for developing and refining measures. Providing concise chapter introductions and summaries, as well as numerous tables, figures, and exhibits, the authors present recommended steps and overlapping activities in a logical, sequential progression. Designed for graduate students in measurement/psychometrics, structural equation modeling, and survey research seminars across the social science discipli

This volume highlights the theory that decisions made during the design of a data collection instrument influence the kind of data and the format of the data that are available for analysis. Opening with a discussion on the selection of the data collection technique(s) and how this impacts on data processing and the data for later analysis, the book covers key issues such as: should you create your own instrument for a questionnaire? how do you test a questionnaire? what are the characteristics of good data processing? how to deal with missing data? how to scale an evaluation and create subfiles for analysis? In addition, each major section concludes with examples and when appropriate, directs the reader to commonly available computer software that can aid in data processing.

* Student evaluations of college teachers: perhaps the most contentious issue on campus* This book offers a more balanced approach* Evaluation affects pay, promotion and tenure, so of intense interest to all faculty* Major academic marketing and publicity* Combines original research with Berk’s signature wacky humorTo many college professors the words "student evaluations" trigger mental images of the shower scene from Psycho, with those bloodcurdling screams. They’re thinking: "Why not just whack me now, rather than wait to see those ratings again." This book takes off from the premise that student ratings are a necessary, but not sufficient source of evidence for measuring teaching effectiveness. It is a fun-filled--but solidly evidence-based--romp through more than a dozen other methods that include measurement by self, peers, outside experts, alumni, administrators, employers, and even aliens. As the major stakeholders in this process, both faculty AND administrators, plus clinicians who teach in schools of medicine, nursing, and the allied health fields, need to be involved in writing, adapting, evaluating, or buying items to create the various scales to measure teaching performance. This is the first basic introduction in the faculty evaluation literature to take you step-by-step through the process to develop these tools, interpret their scores, and make decisions about teaching improvement, annual contract renewal/dismissal, merit pay, promotion, and tenure. It explains how to create appropriate, high quality items and detect those that can introduce bias and unfairness into the results.Ron Berk also stresses the need for “triangulation”--the use of multiple, complementary methods--to provide the properly balanced, comprehensive and fair assessment of teaching that is the benchmark of employment decision making.This is a must-read to empower faculty, administrators, and clinicians to use appropriate evidence to make decisions accurately, reliably, and fairly. Don’t trample each other in your stampede to snag a copy of this book!

It is observed that Researchers face a lot of difficulties in planning, design, collection, analysis and interpretation of Likert Scale data. Therefore, as an aid for the researchers it is attempted to write a book entitled 'A Comprehensive Guide for Design, Collection, Analysis and Presentation of Likert and other Rating Scale Data' on this subject with the following chapters 1. Basics of Likert Scale 2. General Issues of Likert Scaling 3. Templates for Creating Likert Scales 4. Basic Concepts of Measurement 5. Analysis of Likert Data 6. Appropriate Chart or Graph for Likert scale 7. Likert Scale Data Analysis with Statistical Software.This book discusses various efforts to identify, collect, analyse, improve, and present Likert data collected by rating scales such as Likert Scale. Most importunately the book illustrates, review, and critique several forms of collection, analysis, graphical presentation and interpretation of results from studies using rating scales. The most salient and striking features covered in this book are as followsDifferences between Likert-type or Likert scale dataLikert-type data is an ordinal data, therefore, non-parametric tests such as Mann Whitney-U test, Wilcoxon signed-rank test, Kruskal-Wallis test should be used in lieu of parametric tests.Likert scale data, on the other hand, are analysed as interval data. and analysis that can be performed includes mean for central tendency, standard deviations for variability, Pearson's r for bivariate analysis, t-test and ANOVA for comparing group means, and regression procedures for associations.For Likert-type data mode or median is used for measuring central tendency and frequencies for variability. Analysis appropriate for ordinal scale items that includes the chi-square measure of association, Kendall Tau B, and Kendall Tau C.The dispute over the use of parametric versus non-parametric methods for the analysis of Likert scale ordinal data has raged for the past eight decades is discussed fully and suggested the right one.Focuses on validity, reliability and analysis of the Likert ScalePictorial display of several ways in which statistical data may be presented pictorially such as different types of graphs and diagrams is covered.Demonstration for Calculating Descriptive Statistics, Chi-Square Goodness-of-Fit, Mann-Whitney U Test, Sign Test, Wilcoxon-Mann-Whitney test and Cronbach's alpha with examples using SPSS.

This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.