A primer in longitudinal data analysis /

Mostrar otras versiones (2)

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.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Taris, Toon
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : SAGE, 2000.
Colección:Online access: SAGE SAGE Research Methods Core.
Temas:
Longitudinal method.
Social sciences.
Méthode longitudinale.
Sciences sociales.
social sciences.
SOCIAL SCIENCE > Research.
SOCIAL SCIENCE > Methodology.
Longitudinal method
Social sciences
Aufsatzsammlung
Sozialwissenschaften
Statistik
Longitudinaal onderzoek.
Data-analyse.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Longitudinal data and longitudinal designs
  • Covariation and causation
  • Designs for collecting longitudinal data
  • Nonresponse in longitudinal research
  • Nonresponse in cross-sectional and longitudinal designs
  • Minimizing nonresponse and attrition
  • Detecting selective nonresponse
  • Measuring concepts across time: issues of stability and meaning
  • Types of change and stability
  • Exploratory vs. confirmatory factor analysis
  • Using the confirmatory factor-analytic model to assess structural invariance
  • Issues in discrete-time panel analysis
  • Measuring change in discrete time
  • Dependence on initial values: the sophomore slump
  • Change scores: what is the difference?
  • The regressor variable approach and the return of the difference score
  • Assessing causal direction across time: cross-lagged panel analysis
  • Analysis of repeated measures
  • Examining across-time growth
  • Analysis of variance: some basics
  • Analysis of variance for longitudinal survey data
  • Analyzing durations
  • Survival-, failure time- and event history-analysis
  • Survival data
  • Continuous-time survival analysis: hazard function and survival function
  • Analysis of covariates: the stratification approach
  • Parametric and semi-parametric approaches to analyzing covariates
  • Discrete-time survival analysis
  • Analyzing sequences
  • Event- vs. career-centered modes of analysis
  • Measuring career change: characterizing development
  • Creating classifications of careers: distance-based methods
  • Same-order methods: sequencing careers.

Ejemplares similares