Advanced Multitrait-Multimethod Analyses for the Behavioral and Social Sciences

Herausgeber: Helm, Jonathan Lee

• Gebundenes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: Routledge
• Seitenzahl: 244
• Erscheinungstermin: 20. Juli 2021
• Englisch
• Abmessung: 240mm x 161mm x 18mm
• Gewicht: 536g
• ISBN-13: 9780367336448
• ISBN-10: 0367336448
• Artikelnr.: 69984237

Autorenporträt

Jonathan Lee Helm is an Assistant Professor of quantitative psychology at San Diego State University, California, USA. In general, Dr. Helm develops and refines statistical models that measure psychological constructs, and analyze longitudinal data.

Inhaltsangabe

1 An Introduction to Advanced Multitrait-Multimethod Analysis 2
Multitrait-Multimethod Matrix: Method in the Madness 3 Restricted
Correlated Trait - Correlated Method Models for Analyzing Multitrait -
Multimethod Data 4 Musing on Alternate Confirmatory Factor Models for
Multitrait - Multimethod Data 5 Rank Deficiencies in a Reduced Information
Latent Variable Model 6 Calculating the Probability of Accurate Model
Selection for Multitrait - Multimethod Structural Equation Models 7
Construction of Informative Priors for the Application of CFA - MTMM Models
in Small Samples: A Model - Free Approach 8 Leveraging Component-Based
Methods to Improve MTMM Analysis: Exploration and Outlier Detection 9
Analysing Multitrait-Multimethod Data with Exploratory Multivariate
Analysis...The French Way: A Multiple Factor Analysis Perspective