By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes. However, longitudinal research has many faces. This book examines all the main approaches as well as newer developments (such as structural equation modelling, multilevel modelling and optimal scaling) to enable the reader to gain a thorough understanding of the approach and make appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.
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.
Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
Furthermore, as noted by Allison [1982], the regression coeflicients of the model are invariant to interval length. ... In the ordinal treatment, survival time is represented by the ordered outcome Y,-j, which is designated as being ...
Mojtabai , R. , Nicholson , R. A. , & Neesmith , D. H. ( 1997 ) . Factors affecting relapse in patients discharged from a public hospital : Results from survival analysis . Psychiatric Quarterly , 68 , 117–129 .
From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis Enables students to select the correct statistical methods ...
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.
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.
This text describes regression-based approaches to analyzing longitudinal and repeated measures data.
A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.
Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the ...