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Applied Regression Analysis, Linear Models, and Related Methods by John Fox is a comprehensive resource for understanding and implementing statistical data analysis in social research. This hardcover edition, published by SAGE Publications, Incorporated in 1997, encompasses a broad range of regression analysis techniques, including linear least-squares regression, dummy-variables regression, analysis of variance, and diagnostic methods for assessing the adequacy of linear model fits to data.
The book includes nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences, making it an accessible and detailed guide for both students and professionals. Its 624 pages cover topics such as extensions to linear least squares, including logit and probit models, time-series regression, nonlinear and robust regression, nonparametric regression, and empirical methods for assessing sampling variation through the bootstrap and cross-validation. This text is intended for a scholarly and professional audience.
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