Multilevel Analysis in Obesity Research

  • David Rindskopf
Chapter
Part of the NATO ASI Series book series (NSSA, volume 278)

Abstract

In obesity research it is common to have repeated measures on subjects. Traditional statistical analyses of repeated measures data are analysis of variance (ANOVA) for random effects, and multivariate analysis of variance (MANOVA). Each assume that every subject was measured (i) the same number of times, and (ii) at the same time points. Another typical complication of many research designs is the presence of time-varying covariates. The usual ANOVA approach to repeated measures does not allow such covariates, and the MANOVA approach usually treats them as dependent variables. Hierarchical linear models deal with all of the above issues in a natural manner, making them an important tool for obesity research. This paper discusses some simple hierarchical models, and shows their application using two real data sets.

Keywords

Obesity Covariance Shrinkage 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bryk, A. S., Raudenbush, S. W. (1992) Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage Publications.Google Scholar
  2. Bryk, A. S., Raudenbush, S. W., Seltzer, M. & Congdon, R. (1988) An introduction to HLM: Computer program and user’s guide (2nd ed.). Chicago: University of Chicago Department of Education.Google Scholar
  3. Darlington, D. (1992) Weight loss as a funtion of treatment and personality variables. Unpublished dissertation proposal, CUNY Graduate Center.Google Scholar
  4. Goldstein, H. (1987) Multilevel models in educational and social research. New York: Oxford University Press.Google Scholar
  5. Gornbein, J. A., Lazaro. C. G., & Little, R. J. A. (1992) Incomplete data in repeated measures analysis. Statistical methods in medical research, 1 ,275–295.CrossRefGoogle Scholar
  6. Willett, J. B. (1988). Questions and answers in the measurement of change. In E. Z. Rothkopf (ed.). Review of research in education 15 (pp. 345–422). Washington. DC: American Educational Research Association.Google Scholar

Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • David Rindskopf
    • 1
  1. 1.City University of New York Graduate CenterNew YorkUSA

Personalised recommendations