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Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence

발행사항
NY: OXFORD, 2003
형태사항
612p. , 24cm
서지주기
includes bibliographical references and index
소장정보
위치등록번호청구기호 / 출력상태반납예정일
이용 가능 (1)
한국청소년정책연구원00021574대출가능-
이용 가능 (1)
  • 등록번호
    00021574
    상태/반납예정일
    대출가능
    -
    위치/청구기호(출력)
    한국청소년정책연구원
책 소개
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. 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.

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. 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.