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This work describes several statistical techniques for studying repeated measures data, presenting growth curve methods applicable to biomedical, social, animal, agricultural and business research.
It details the multivariate development of growth science and repeated measures experiments, covering time-moving covariates, exchangable errors, bioassay results, missing data procedures and nonparametric and Bayesian methods.
Growth Curve Models and Applications
Advances in Growth Curve and Structural Equation Modeling
Growth Curve Modeling
Analysis of Longitudinal Data
Higher-Order Growth Curves and Mixture Modeling with Mplus
Growth Curve Analysis and Visualization Using R
Introduction to Latent Variable Growth Curve Modeling
Advances in Growth Curve and Structural Equation Modeling
Statistical Analysis of Human Growth and Development
Methods and Applications of Longitudinal Data Analysis
Analysis of Repeated Measures
Nonlinear Models for Repeated Measurement Data