{"product_id":"analysis-of-multivariate-social-science-data-statistical-machine-learning-methods-paperback","title":"Analysis of Multivariate Social Science Data: Statistical Machine Learning Methods - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eIrini Moustaki\u003c\/b\u003e (Author), \u003cb\u003eFiona Steele\u003c\/b\u003e (Author), \u003cb\u003eYunxiao Chen\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThird Edition enables a basic understanding of how to use key multivariate methods in the social sciences. Authors focus on regression analysis. Provides link between two halves of the book, the move from descriptive to inferential methods, from interdependence to dependence.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eIrini Moustaki\u003c\/b\u003e is a professor of Statistics in the Department of Statistics at the London School of Economics and Political Science. She received her bachelor's degree in Statistics and Computer Science from the Athens University of Economics and Business and her MSc and PhD in Statistics from the LSE. Her research interests are in latent variable models and structural equation models. Her methodological work includes treating missing data, longitudinal data, outlier detection, goodness-of-fit tests, and advanced estimation methods. Furthermore, she has made methodological and applied contributions to comparative cross-national studies and epidemiological studies on rare diseases. Irini received an honorary doctorate from the Faculty of Social Sciences, Uppsala University, in 2014. She is a Fellow of the British Academy. She was the Executive Editor of the journal \u003ci\u003ePsychometrika\u003c\/i\u003e from November 2014 to December 2018 and the President of the Psychometric Society from July 2021 to July 2022.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFiona Steele\u003c\/b\u003e is a Professor of Statistics in the Department of Statistics at the London School of Economics and Political Science (LSE). She holds a Ph.D. in Social Statistics from the University of Southampton. Her research interests are in developments of statistical methods that are motivated by social science problems. Her areas of expertise include longitudinal data analysis, multilevel and latent variable modelling, and dyadic data analysis. She has worked on a range of applications in demography, education, family psychology and health. Fiona has directed several research grants on methods for multilevel and longitudinal data analysis. She also led the development of, and contributed modules to, the popular online 'LEMMA' course on multilevel modelling. Fiona is a Fellow of the British Academy and was awarded a CBE and the Royal Statistical Society Howard Medal for her contributions to social statistics. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eYunxiao Chen\u003c\/b\u003e is an Associate Professor of Statistics in the Department of Statistics at the London School of Economics and Political Science (LSE). He holds a Ph.D. in Statistics from Columbia University in the City of New York. His research focuses on the intersection of multivariate statistics and machine learning, where he develops models, computational algorithms, and statistical theories for learning from complex data and applies them to education, psychology, and other social science disciplines. Dr. Chen has received numerous awards, including the 2018 Brenda H. Lloyd Dissertation Award from the National Council on Measurement in Education and the 2022 Early Career Award from the Psychometric Society. He was also a Spencer Foundation\/NAEd Postdoctoral Fellow at the United States National Academy of Education from 2018 to 2020. His work has appeared in leading journals in statistics and machine learning, such as the \u003ci\u003eJournal of the American Statistical Association\u003c\/i\u003e, \u003ci\u003eBiometrika\u003c\/i\u003e, \u003ci\u003eJournal of the Royal Statistical Society, Series A (Statistics in Society)\u003c\/i\u003e, and the \u003ci\u003eJournal of Machine Learning Research\u003c\/i\u003e. Additionally, Dr. Chen serves as an associate editor for several prominent publications, including \u003ci\u003ePsychometrika\u003c\/i\u003e, the \u003ci\u003eBritish Journal of Mathematical and Statistical Psychology\u003c\/i\u003e, the\u003ci\u003e Journal of Educational and Behavioural Statistics\u003c\/i\u003e, and \u003ci\u003ePsychological Methods\u003c\/i\u003e. This book, \u003ci\u003eAnalysis of Multivariate Social Science Data: Statistical Machine Learning Methods\u003c\/i\u003e, draws on his years of experience teaching and researching in the field. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eDavid John Bartholomew\u003c\/b\u003e was a professor of Statistics in the Department of Statistics at the London School of Economics and Political Science from 1973 to 1996, when he became an emeritus professor. His research interests were in the areas of stochastic modelling, social measurement, factor analysis and latent variable modelling. Bartholomew published some 25 books and more than 140 research papers. He served as pro-director of the LSE from 1988 to 1991. He served as co-editor of the \u003ci\u003eJournal of the Royal Statistical Society, Series B\u003c\/i\u003e, from 1966 to 1969 and president from 1993 to 1995. He was awarded the Guy medal in bronze in 1971. He was elected a fellow of the British Academy in 1987. Professor Bartholomew passed away in 2017.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 481\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e February 10, 2026\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":46185765798023,"sku":"9781032763729","price":118.24,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0601\/2623\/2711\/files\/97wqXMdBZZ9781032763729.webp?v=1792018217","url":"https:\/\/booksby.splitshops.com\/products\/analysis-of-multivariate-social-science-data-statistical-machine-learning-methods-paperback","provider":"Books by splitShops","version":"1.0","type":"link"}