Unusual book
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Niall Bolger, PhD, is Professor and Chair of Psychology at Columbia University, USA. He is a Charter Member and Fellow of the Association for Psychological Science and a Fellow of the Society of Experimental Social Psychology and the Society for Personality and Social Psychology. Dr. Bolger studies adjustment processes in close relationships, using intensive longitudinal methods and laboratory-based studies of dyadic behavior, emotion, and physiology. He also studies personality processes as they are revealed in patterns of behavior, emotion, and physiology in daily life. Finally, he is interested in statistical methods for analyzing longitudinal and multilevel data.
Jean-Philippe Laurenceau, PhD, is Professor of Psychology at the University of Delaware, USA. He is an appointed member of the Social, Personality, and Interpersonal Processes grant review panel of the National Institutes of Health. Dr. Laurenceau's research focuses on understanding the processes by which partners in marital and romantic relationships develop and maintain intimacy in the context of everyday life. His methodological interests include intensive longitudinal methods for studying close relationship processes and applications of modern methods for the analysis of change in individuals and dyads.
This book offers a complete, practical guide to doing an intensive longitudinal study with individuals, dyads, or groups. It provides the tools for studying social, psychological, and physiological processes in everyday contexts, using methods such as diary and experience sampling. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, apply multilevel models to within-subject designs, model within-subject change processes for continuous and categorical outcomes, assess the reliability of within-subject changes, assure sufficient statistical power, and more. Several end-of-chapter write-ups illustrate effective ways to present study findings for publication. Datasets and output in SPSS, SAS, Mplus, HLM, MLwiN, and R for the examples are available on the companion website ( www.intensivelongitudinal.com).
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. This book offers a complete, practical guide to doing an intensive longitudinal study with individuals, dyads, or groups. It provides the tools for studying social, psychological, and physiological processes in everyday contexts, using methods such as diary and experience sampling. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, apply multilevel models to within-subject designs, model within-subject change processes for continuous and categorical outcomes, assess the reliability of within-subject changes, assure sufficient statistical power, and more. Several end-of-chapter write-ups illustrate effective ways to present study findings for publication. Datasets and output in SPSS, SAS, Mplus, HLM, MLwiN, and R for the examples are available on the companion website (). A complete, practical guide to planning and executing an intensive longitudinal study, this book provides the tools for understanding within-subject social, psychological, and physiological processes in everyday contexts. Intensive longitudinal studies involve many repeated measurements taken on individuals, dyads, or groups, and include diary and experience sampling studies. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, model within-subject change processes for continuous and categorical outcomes, distinguish within-subject from between-subjects effects, assess the reliability of within-subject changes, assure sufficient statistical power, and more. Several end-of-chapter write-ups illustrate effective ways to present study findings for publication. Datasets and output for the examples are available for readers' use at the companion website. The website also includes HLM, MLwin, and R code as an alternative to the SPSS, SAS, and Mplus code presented in the book. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781462506781
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