Finch, W. Holmes (William Holmes) creator author. text Boca Raton CRC 2022 First edition. monographic eng vii, 297p. "Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, Applied Regularization Methods for the Social Sciences provides and overview of a variety of models alongside clear examples of hands-on application. Each chapter in this book covers a specific application of regularization techniques with a user-friendly technical description, followed by examples that provide a thorough demonstration of the methods in action"-- R -- Theoretical underpinnings of regularization methods -- Regularization methods for linear models -- Regularization methods for generalized linear models -- Regularization methods for multivariate linear models -- Regularization methods for cluster analysis and principal components analysis -- Regularization methods for latent variable models -- Regularization methods for multilevel models. Holmes Finch. Includes bibliographical references and index. English. Social sciences Statistical methods Big data Mathematical statistics R (Computer program language) 300.15 FIN-A 9781032209470