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GMANOVA is frequently used for the analysis of surveys, clinical trials, and agricultural data, [7] as well as more recently in the context of Radar adaptive detection. In mathematical statistics , growth curves such as those used in biology are often modeled as being continuous stochastic processes , e.

Detection of Outliers in Growth Curve Models: Using Robust Estimators

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Growth Curve Models and Statistical Diagnostics

Statistics: Textbooks and Monographs Second ed. Advanced multivariate statistics with matrices. Mathematics and its applications.


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    Growth-curve models are generalized multivariate analysis-of-variance models. The basic idea of the models is to use different polynomials to fit different treatment groups involved in the longitudinal study. It is not uncommon, however, to find outliers and influential observations in growth data that heavily affect statistical inference in growth curve models.

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    This book provides a comprehensive introduction to the theory of growth curve models with an emphasis on statistical diagnostics. A variety of issues on model fittings and model diagnostics are addressed, and many criteria for outlier detection and influential observation identification are created within likelihood and Bayesian frameworks.