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Informationen zum Autor Karen Robson is Assistant Professor in the Department and Marketing and Hospitality at Central Michigan University. She holds a BSc (Honsd) in Psychology from Queen’s University, and an MA in Psychology, an MBA and PhD from Simon Fraser University. Karen’s research investigates consumer innovativeness, including how consumers repurpose or use market offerings in ways not intended by the manufacturer and the intellectual property law implications of this practice. A recipient of the Joseph-Armand Bombardier Doctoral Scholarship, her work has appeared in journals such as MIS Quarterly Executive , Business Horizons , Journal of Marketing Education , Journal of Advertising Research , and Journal of Public Affairs . David Pevalin is Professor in the School of Health and Human Sciences and Dean of Postgraduate Research and Education at the University of Essex. He previously served in the Merchant Navy, the City of London Police and the Royal Hong Kong Police. He studied part time at the University of Hong Kong before graduate studies at the University of Calgary, Canada. He returned to the UK in 1999 as Senior Research Officer at the Institute for Social and Economic Research at the University of Essex and joined his current School in 2003 after obtaining his PhD. He co-authored (with Karen Robson) The Stata Survival Manual (Open University Press), co-edited (with David Rose) The Researcher’s Guide to the National Statistics Socio-economic Classification (Sage), and authored research reports for the Department of Work and Pensions and the Health Development Agency. He has published papers in the Journal of Health and Social Behavior , British Journal of Sociology , Lancet , Public Health , and Housing Studies . Klappentext With a real focus on the practical, this book provides students with a step-by-step approach, plenty of real-life examples, and downloadable data and exercises on the accompanying study website to help take the fear and intimidation out of multilevel modeling Zusammenfassung With a real focus on the practical! this book provides students with a step-by-step approach! plenty of real-life examples! and downloadable data and exercises on the accompanying study website to help take the fear and intimidation out of multilevel modeling Inhaltsverzeichnis Chapter 1: What Is Multilevel Modeling and Why Should I Use It? Mixing levels of analysis Theoretical reasons for multilevel modeling What are the advantages of using multilevel models? Statistical reasons for multilevel modeling Assumptions of OLS Software How this book is organized Chapter 2: Random Intercept Models: When intercepts vary A review of single-level regression Nesting structures in our data Getting starting with random intercept models What do our findings mean so far? Changing the grouping to schools Adding Level 1 explanatory variables Adding Level 2 explanatory variables Group mean centring Interactions Model fit What about R-squared? R-squared? A further assumption and a short note on random and fixed effects Chapter 3: Random Coefficient Models: When intercepts and coefficients vary Getting started with random coefficient models Trying a different random coefficient Shrinkage Fanning in and fanning out Examining the variances A dichotomous variable as a random coefficient More than one random coefficient A note on parsimony and fitting a model with multiple random coefficients A model with one random and one fixed coefficient Adding Level 2 variables Residual diagnostics First steps in model-building Some tasters of further extensions to our basic models...
