Modeling Longitudinal and Multilevel Data
Regular price
€71.99
14 days return policy
Shipping & Delivery
Category=GPS
Category=JHB
Category=JMB
Category=PBT
curve
DA
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
equation
full
Full Information Maximum Likelihood Approach
Full Information Maximum Likelihood Estimate
graduate research methods
growth
Growth Curve Models
information
Intra-individual Change
Intraindividual Change
latent
Latent Class
Latent Curve Modeling
latent growth analysis
Latent Growth Model
Latent Transition Analysis Model
Latent Variable
LD
likelihood
longitudinal SEM applications
MAR Data
maximum
Measurement Occasion
Missing Data
missing data techniques
models
Multilevel Model
Multilevel Regression
Multilevel Regression Model
Multilevel SEM
multivariate change modeling
PD
Regression Model
Regression Weights
SEM
SEM Program
stage-sequential change
structural
Structural Equation Model
structural equation modeling
Product details
- ISBN 9781138012530
- Weight: 408g
- Dimensions: 152 x 229mm
- Publication Date: 22 Dec 2014
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
Secure
checkout
Fast Shipping
Easy returns
This book focuses on the practical issues and approaches to handling longitudinal and multilevel data. All data sets and the corresponding command files are available via the Web. The working examples are available in the four major SEM packages--LISREL, EQS, MX, and AMOS--and two Multi-level packages--HLM and MLn. All equations and figural conventions are standardized across each contribution. The material is accessible to practicing researchers and students. Users can compare and contrast various analytic approaches to longitudinal and multiple-group data including SEM, Multi-level, LTA, and standard GLM techniques. Ideal for graduate students and practicing researchers in social and behavioral sciences.
Todd D. Little (Edited by) , Kai U. Schnabel (Edited by) , Jurgen Baumert (Edited by)
