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This volume is focused on the social intelligence (SI) of leaders. SI is generally defined as the ability to be aware of relevant social situational contexts; to deal with the contexts or challenges effectively; to understand others’ concerns, feelings, and emotional states; and to interact appropriately in social situations and build and maintain positive relationships with others. Beginning with a cross-cultural study of the social intelligence of leaders in the United States, the United Kingdom, Scotland, Hong Kong, and Thailand, the work moves on to discuss the influence of SI on creative performance. The findings of the study show that leaders’ SI was positively associated with their creative performance in each of the five countries. Other contributions cover topics relating to SI such as social connection and executive compassion. In addition, the volume also features five book reviews, a list of books received, and a detailed case study, titled “Program Management for Global Software Development: A Case Study of the Windows Embedded Automotive Team” by Paul Gratton. The work will be of use to those studying business, management, and economics.
Companion Website materials: https://tzkeith.com/ Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. This book: • Covers both MR and SEM, while explaining their relevance to one another • Includes path analysis, confirmatory factor analysis, and latent growth modeling • Makes extensive use of real-world research examples in the chapters and in the end-of-chapter exercises • Extensive use of figures and tables providing examples and illustrating key concepts and techniques New to this edition: • New chapter on mediation, moderation, and common cause • New chapter on the analysis of interactions with latent variables and multilevel SEM • Expanded coverage of advanced SEM techniques in chapters 18 through 22 • International case studies and examples • Updated instructor and student online resources
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Critics of student self-reported data claim that the accumulated corpus of research documenting student learning on the basis of survey responses stands on shaky ground. This volume argues that scholarship on proper use of student self-report data is woefully underdeveloped and contributing authors offer several important insights to assist IR practitioners in identifying potential limitations associated with self-report data. Volume editors Serge Herzog, director of institutional analysis at the University of Nevada, Reno, and Nicholas A. Bowman, postdoctoral research associate in the Center for Social Concerns at the University of Notre Dame, have assembled contributing authors who are leading scholars in the field of college student self-reports. Combined, the chapters draw on data from a mix of colleges and universities, capturing student growth at different stages of the undergraduate experience, and even beyond graduation. This is the 150th volume of the Jossey-Bass quarterly report series New Directions for Institutional Research. Always timely and comprehensive, New Directions for Institutional Research provides planners and administrators in all types of academic institutions with guidelines in such areas as resource coordination, information analysis, program evaluation, and institutional management.
Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions.