Buch, Englisch, 242 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 534 g
Buch, Englisch, 242 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 534 g
Reihe: European Association of Methodology Series
ISBN: 978-0-367-33644-8
Verlag: Routledge
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.
Zielgruppe
Postgraduate and Professional
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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