(Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
by Holmes Finch (Author)
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.
Key Features:
- Description of regularization methods in a user friendly and easy to read manner
- Inclusion
of regularization-based approaches for a variety of statistical
analyses commonly used in the social sciences, including both univariate
and multivariate models
- Fully developed extended examples using multiple software packages, including R, SAS, and SPSS
- Inclusion of both frequentist and Bayesian regularization approaches
- Application
exercises for each chapter that instructors could use in class, and
independent researchers could use to practice what they have learned
from the book
