Description: Machine Learning for Social and Behavioral Research, Hardcover by Jacobucci, Ross; Grimm, Kevin J.; Zhang, Zhiyong, ISBN 1462552935, ISBN-13 9781462552931, Brand New, Free shipping in the US Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. Th covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for th's examples.
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Book Title: Machine Learning for Social and Behavioral Research
Number of Pages: 416 Pages
Publication Name: Machine Learning for Social and Behavioral Research
Language: English
Publisher: Guilford Publications
Subject: Nursing / Research & Theory, Research, Statistics
Item Height: 0.9 in
Publication Year: 2023
Item Weight: 33.4 Oz
Type: Textbook
Item Length: 10 in
Author: Kevin J. Grimm, Zhiyong Zhang, Ross Jacobucci
Subject Area: Social Science, Education, Psychology, Medical
Item Width: 7 in
Series: Methodology in the Social Sciences Ser.
Format: Hardcover
