• Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Dynamic Mixed Models for Familial Longitudinal Data

Dynamic Mixed Models for Familial Longitudinal Data

Paperback

Series: Springer Statistics

Medical ReferenceProbability & StatisticsComputer Security

ISBN10: 1461428017
ISBN13: 9781461428015
Publisher: Springer
Published: Apr 19 2013
Pages: 494
Weight: 1.56
Height: 1.03 Width: 6.14 Depth: 9.21
Language: English

This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that accommodates all possible Gaussian type auto-correlation models as special cases including the equi-correlation models. This new dynamic modelling approach is utilized to develop theoretically sound inference techniques such as the generalized quasi-likelihood (GQL) technique for consistent and efficient estimation of the underlying regression effects involved in the model, whereas the existing 'working' correlations based GEE (generalized

1 different editions

Also available

Also in

Probability & Statistics