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Statistics for the social and behavioral sciences

Science & Math

Kenny, David A.

Behavioral Sciences

Little,Brown

Correlation and Causality, by David A. Kenny, is a general introduction to the topic of structural analysis that presumes no previous acquaintance with causal analysis It also assumes reader has some familiarity with multiple regression and factor analysis Kenny's book, Correlation and Causality, introduced many to Structural Equation Modeling, and his most widely cited influential contributions have been in the area of mediational models

Correlation and Causality

Health, Fitness & Dieting

Psychology & Counseling

John Wiley&Sons, Inc.

Estimating the Effects of Social Intervention

Judd, Charles M.

Cambridge University Press

Statistics for Social and Behavioral Sciences

Politics & Social Sciences

Social Sciences

Scott, Foresman Co.

This book has been replaced by Interpersonal Perception, Second Edition, ISBN 978-1-4625-4151-5.

Interpersonal Perception: A Social Relations Analysis (Distinguished Contributions in Psychology)

Mental Health

The Guilford Press

People make judgments about others all the time, often without realizing they are doing so. How are interpersonal impressions formed? How accurate are our perceptions of other people's traits--and our own? In this major revision of his landmark work, David A. Kenny provides a reader-friendly examination of these and other critical questions, identifying key components that shape impressions and their accuracy. Topics include how to estimate perceiver, target, and relationship effects; the extent to which different perceivers see a target in the same way; the impact of group membership and stereotypes; and whether others see us as we see ourselves. Implications for interpersonal relationships and social behavior are highlighted. New to This Edition *Virtually a new book; incorporates 25 years of theoretical, empirical, and methodological advances. *New and greatly expanded topics, including first impressions, individual differences in accuracy, implicit measures, and narcissism. *Grounded in a reformulated conceptual model. *More accessible--uses nontechnical language, humor, popular culture, and simplified figures to elucidate complex ideas. *End-of-chapter "Practical Suggestions" apply the science to real-world social situations.

Interpersonal Perception: The Foundation of Social Relationships

Self-Help

Relationships

Dyadic Data Analysis (Methodology in the Social Sciences)

Interpersonal phenomena such as attachment, conflict, person perception, learning, and influence have traditionally been studied by examining individuals in isolation, which falls short of capturing their truly interpersonal nature. This book offers state-of-the-art solutions to this age-old problem by presenting methodological and data-analytic approaches useful in investigating processes that take place among dyads: couples, coworkers, parent and child, teacher and student, or doctor and patient, to name just a few. Rich examples from psychology and across the behavioral and social sciences help build the researcher's ability to conceptualize relationship processes; model and test for actor effects, partner effects, and relationship effects; and model and control for the statistical interdependence that can exist between partners. The companion website provides clarifications, elaborations, corrections, and data and files for each chapter.

Dyadic Data Analysis (Methodology in the Social Sciences Series)

Kashy, Deborah A.

Cook, William L.

A Primer on Regression Artifacts

Regression toward the mean is a complex statistical principle that plays a crucial role in any research involving the measurement of change. This primer is designed to help researchers more fully understand this phenomenon and avoid common errors in interpretation. The book presents new methods of graphing regression toward the mean, facilitating comprehension with a wealth of figures and diagrams. Special attention is given to applications related to program or treatment evaluation. Numerous concrete examples illustrate the ways researchers all too often attribute effects to an intervention or other causal variable without considering regression artifacts as an alternative explanation for change. Also discussed are instances when problems are actually created, instead of solved, by "correction" for regression toward the mean. Throughout, the authors strive to use nontechnical language and to keep simulations and formulas as accessible as possible.

Campbell, Donald T.

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Books by Kenny, David A.