Advanced Multitrait-Multimethod Analyses for the Behavioral and Social Sciences

著者名：Helm, Jonathan Lee (EDT)

Routledge（2021/07/19発売）

• 言語：ENG
• ISBN：9780367336424
• eISBN：9781000404098

Description

This book summarizes a range of new analytic tools for multitrait-multimethod (MTMM) data. Providing an expository yet accessible approach to cutting-edge developments for MTMM analysis, a selection of quantitative researchers reveal their recent contributions to the field including non-technical summaries and empirical examples.

The contributions inform quantitative social scientists of some of the most cutting-edge developments for MTMM analysis. A range of developments have emerged over the past decade for MTMM analyses, and this book presents these novel additions to the quantitative community as a cohesive narrative. This book makes these recent MTMM contributions accessible to applied researchers (most MTMM innovations are presented in less approachable journals for applied researchers) by providing non-technical summaries and empirical examples.

This book will serve as a stepping stone for applied researchers seeking to adopt MTMM analysis into their program of research, and will be relevant to researchers, both within a professional and academic context, across the social and behavioral sciences.

Table of Contents

1. An Introduction to Advanced Multitrait-Multimethod Analysis

Jonathan Lee Helm

2. Multitrait-Multimethod Matrix: Method in the Madness

David A. Kenny

3. Restricted Correlated Trait - Correlated Method Models for Analyzing Multitrait - Multimethod Data

Michael Eid, Jana Holtmann, and Tobias Koch

4. Musing on Alternate Confirmatory Factor Models for Multitrait - Multimethod Data

Keith F. Widaman

5. Rank Deficiencies in a Reduced Information Latent Variable Model

Daniel Oberski

6. Calculating the Probability of Accurate Model Selection for Multitrait - Multimethod Structural Equation Models

Jonathan Lee Helm

7. Construction of Informative Priors for the Application of CFA - MTMM Models in Small Samples: A Model - Free Approach

Tobias Koch, Jana Holtmann, and Johannes Heekerens

8. Leveraging Component-Based Methods to Improve MTMM Analysis: Exploration and Outlier Detection

Laura Castro-Schilo

9. Analysing Multitrait-Multimethod Data with Exploratory Multivariate Analysis…The French Way: A Multiple Factor Analysis Perspective

Sébastien Lê