Skip to main content
padlock icon - secure page this page is secure

Multilevel Modelling of Hierarchical Data in Developmental Studies

Buy Article:

$59.00 + tax (Refund Policy)

This report attempts to give nontechnical readers some insight into how a multilevel modelling framework can be used in longitudinal studies to assess contextual influences on child development when study samples arise from naturally formed groupings. We hope to achieve this objective by: (1) discussing the types of variables and research designs used for collecting developmental data; (2) presenting the methods and data requirements associated with two statistical approaches to developmental data—growth curve modelling and discrete-time survival analysis ; (3) describing the multilevel extensions of these approaches, which can be used when the study of development includes intact clusters or naturally formed groupings; (4) demonstrating the flexibility of these two approaches for addressing a variety of research questions; and (5) placing the multilevel framework developed in this report in the context of some important issues, alternative approaches, and recent developments. We hope that readers new to these methods are able to visualize the possibility of using them to advance their work.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Longitudinal studies; development; growth curve analysis; multilevel models; survival analysis

Document Type: Research Article

Affiliations: 1: McMaster University and Hamilton Health Sciences Corporation, Hamilton, Canada, 2: University of New Brunswick, Fredericton, Canada

Publication date: January 1, 2001

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more