The Analysis of Correlation in Longitudinal and Spatial Data
Author : Christl Ann Donnelly
Publisher :
Page : 208 pages
File Size : 27,94 MB
Release : 1992
Category : Correlation (Statistics)
ISBN :
Author : Christl Ann Donnelly
Publisher :
Page : 208 pages
File Size : 27,94 MB
Release : 1992
Category : Correlation (Statistics)
ISBN :
Author : Timothy G. Gregoire
Publisher : Springer Science & Business Media
Page : 404 pages
File Size : 40,43 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 1461206995
Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October 1996 a group of 210 statisticians and other scientists assembled on the small island of Nantucket, U. S. A. , to present and discuss new developments relating to Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Direc tions. Its purpose was to provide a cross-disciplinary forum to explore the commonalities and meaningful differences in the source and treatment of such data. This volume is a compilation of some of the important invited and volunteered presentations made during that conference. The three days and evenings of oral and displayed presentations were arranged into six broad thematic areas. The session themes, the invited speakers and the topics they addressed were as follows: • Generalized Linear Models: Peter McCullagh-"Residual Likelihood in Linear and Generalized Linear Models" • Longitudinal Data Analysis: Nan Laird-"Using the General Linear Mixed Model to Analyze Unbalanced Repeated Measures and Longi tudinal Data" • Spatio---Temporal Processes: David R. Brillinger-"Statistical Analy sis of the Tracks of Moving Particles" • Spatial Data Analysis: Noel A. Cressie-"Statistical Models for Lat tice Data" • Modelling Messy Data: Raymond J. Carroll-"Some Results on Gen eralized Linear Mixed Models with Measurement Error in Covariates" • Future Directions: Peter J.
Author : Garrett Fitzmaurice
Publisher : CRC Press
Page : 633 pages
File Size : 42,13 MB
Release : 2008-08-11
Category : Mathematics
ISBN : 142001157X
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
Author : Toon Taris
Publisher : SAGE
Page : 180 pages
File Size : 23,20 MB
Release : 2000-11-13
Category : Mathematics
ISBN : 9780761960270
Toon Taris' survival guide takes the reader through the strengths and weaknesses of longitudinal research, making clear how to design a longitudinal study, how to collect data most effectively and how to interpret results.
Author : You-Gan Wang
Publisher : CRC Press
Page : 248 pages
File Size : 38,35 MB
Release : 2022-01-28
Category : Mathematics
ISBN : 1498764622
Development in methodology on longitudinal data is fast. Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians to the updated methods on correlated data inference. This book will present a discussion of the modern approaches to inference, including the links between the theories of estimators and various types of efficient statistical models including likelihood-based approaches. The theory will be supported with practical examples of R-codes and R-packages applied to interesting case-studies from a number of different areas. Key Features: •Includes the most up-to-date methods •Use simple examples to demonstrate complex methods •Uses real data from a number of areas •Examples utilize R code
Author : Peter Diggle
Publisher : Oxford University Press, USA
Page : 397 pages
File Size : 29,22 MB
Release : 2013-03-14
Category : Language Arts & Disciplines
ISBN : 0199676755
This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.
Author : Richard .H. Jones
Publisher : CRC Press
Page : 250 pages
File Size : 11,94 MB
Release : 2018-05-04
Category : Mathematics
ISBN : 1351434624
This monograph is written for students at the graduate level in biostatistics, statistics or other disciplines that collect longitudinal data. It concentrates on the state space approach that provides a convenient way to compute likelihoods using the Kalman filter.
Author : Nan M. Laird
Publisher : IMS
Page : 168 pages
File Size : 17,16 MB
Release : 2004
Category : Mathematics
ISBN : 9780940600607
Author : You-Gan Wang
Publisher : CRC Press
Page : 213 pages
File Size : 39,6 MB
Release : 2022-01-28
Category : Mathematics
ISBN : 1351649671
Development in methodology on longitudinal data is fast. Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians to the updated methods on correlated data inference. This book will present a discussion of the modern approaches to inference, including the links between the theories of estimators and various types of efficient statistical models including likelihood-based approaches. The theory will be supported with practical examples of R-codes and R-packages applied to interesting case-studies from a number of different areas. Key Features: •Includes the most up-to-date methods •Use simple examples to demonstrate complex methods •Uses real data from a number of areas •Examples utilize R code
Author : Jeffrey D. Long
Publisher : SAGE
Page : 569 pages
File Size : 28,95 MB
Release : 2012
Category : Mathematics
ISBN : 1412982685
This book is a practical guide for the analysis of longitudinal behavioural data. Longitudinal data consist of repeated measures collected on the same subjects over time.