Applied Longitudinal Data Analysis
Modeling Change and Event Occurrence
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Product details:
- Publisher OUP Oxford
- Date of Publication 8 May 2003
- ISBN 9780195152968
- Binding Hardback
- No. of pages672 pages
- Size 242x164x35 mm
- Weight 1039 g
- Language English
- Illustrations Numerous tables and figures 0
Categories
Short description:
The investigation of change has fascinated empirical researchers for generations, and to do it well, they must have longitudinal data. This much-needed professional book will instruct readers in the many new methodologies now at their disposal to make the best use of longitudinal data, including both individual growth modeling and survival analysis, making it a unique contribution to the literature on research methods. The authors employ many cases and examples from a variety of disciplines, covering multilevel models, curvilinear and discontinuous change, in addition to discrete-time hazard models, continuous-time event occurrence, and Cox regression models.
MoreLong description:
Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. In addition to these natural changes, targeted interventions may cause change: cholesterol levels may decline as a result of a new medication, exam grades may rise following completion of a coaching class. By measuring and charting changes like these - both naturalistic and experimentally induced - researchers uncover the temporal nature of development. The investigation of change has fascinated empirical researchers for generations, and to do it well, they must have longitudinal data.
Applied Longitudinal Data Analysis is a much-needed professional book that will instruct readers in the many new methodologies now at their disposal to make the best use of longitudinal data, including both individual growth modelling and survival analysis. Throughout the chapters, the authors employ many cases and examples from a variety of disciplines, covering multilevel models, curvilinear and discontinuous change, in addition to discrete-time hazard models, continuous-time event occurrence, and Cox regression models. Applied Longitudinal Data Analysis is a unique contribution to the literature on research methods and will be useful to a wide range of behavioural and social science researchers.
Table of Contents:
Part I
A framework for investigating change over time
Exploring Longitudinal Data on Change
Introducing the multilevel model for change
Doing data analysis with the multilevel mode for change
Treating TIME more flexibly
Modelling discontinuous and nonlinear change
Examining the multilevel model's error covariance structure
Modelling change using covariance structure analysis
Part II
A Framework for Investigating Event Occurrence
Describing discrete-time event occurrence data
Fitting basic Discrete-Time Hazard Models
Extending the Discrete-Time Hazard Model
Describing Continuous-Time Event Occurrence Data
Fitting Cox Regression Models
Extending the Cox Regression Model
