Longitudinal data analysis using structural equation models
Title Statements
- Full title :Longitudinal data analysis using structural equation models / John J. McArdle, John R. Nesselroade.
Edition Statements
- Publication Date:cop. 2014.
Publication Statements
- Publisher(s):American Psychological Association
- Place of Publication:Washington, DC
- Language:eng
- Publication Date:cop. 2014.
The Physical Object
- Description:xi, 426 p. : : ill. ; : 26 cm
Edition Identifiers
- ISBN:1433817152, 9781433817151
- oclc:ocn888442037
- LC Classification:BF76.6.L65
- Dewey Decimal:150.72/1
Table of Contents
Preface -- Overview -- Foundations -- Background and goals of longitudinal research -- Basics of structural equation modeling -- Some technical details on structural equation modeling -- Using the simplified ram notation -- Benefits and problems of longitudinal structure modeling -- The first purpose of LSEM : direct identification of intra-individual changes -- Alternative definitions of individual changes -- Analyses based on latent curve models (LCM) -- Analyses based on time series regression (TSR) -- Analyses based on latent change score (LCS) models -- Analyses based on advanced latent change score models -- The second purpose of LSEM : identification of inter-individual differences in intra-individual changes -- Studying inter-individual differences in intra-individual changes -- Repeated measures analysis of variance as a structural model -- Multi-level structural equation modeling approaches to group differences -- Multi-group structural equation modeling approaches to group differences -- Incomplete data with multiple group modeling of changes -- The third purpose of LSEM : identification of inter-relationships in growth -- Considering common factors/latent variables in …
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