Description - An R and S-PLUS Companion to Applied Regression by John Fox
'This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. it meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics and useful instructions on writing customized functions' - Jeff Gill, University of Florida, Gainesville
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(254mm x 177mm x 19mm)
SAGE Publications Inc
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Author Biography - John Fox
John Fox is Professor of Sociology at McMaster University in Hamilton, Ontario, Canada. He was previously Professor of Sociology and of Mathematics and Statistics at York University in Toronto, where he also directed the Statistical Consulting Service at the Institute for Social Research. Professor Fox earned a Ph.D. in Sociology from the University of Michigan in 1972. He has delivered numerous lectures and workshops on statistical topics, at such places as the summer program of the Inter-University Consortium for Political and Social Research and the annual meetings of the American Sociological Association. His recent and current work includes research on statistical methods (for example, work on three-dimensional statistical graphs) and on Canadian society (for example, a study of political polls in the 1995 Quebec sovereignty referendum). He is author of many articles, in such journals as Sociological Methodology, The Journal of Computational and Graphical Statistics, The Journal of the American Statistical Association, The Canadian Review of Sociology and Anthropology, and The Canadian Journal of Sociology. He has written several other books, including Applied Regression Analysis, Linear Models, and Related Methods (Sage, 1997), Nonparametric Simple Regression (Sage, 2000), and Multiple and Generalized Nonparametric Regression (Sage, 2000).