Series:

Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

2 total works

Cover of Multilevel Modeling Using Mplus

Multilevel Modeling Using Mplus

by Holmes Finch

Published 22 December 2016
This book is designed primarily for upper level undergraduate and graduate level students taking a course in multilevel modelling and/or statistical modelling with a large multilevel modelling component. The focus is on presenting the theory and practice of major multilevel modelling techniques in a variety of contexts, using Mplus as the software tool, and demonstrating the various functions available for these analyses in Mplus, which is widely used by researchers in various fields, including most of the social sciences. In particular, Mplus offers users a wide array of tools for latent variable modelling, including for multilevel data.

Cover of Applied Regularization Methods for the Social Sciences

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
  • Website containing all datasets and software scripts used in the examples
  • 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