We discuss the analysis of growth curve data with missing or incomplete information. The approach is to fit subject-specific models and then to carry out an analysis in terms of the estimated parameters. This achieves reduction of data and eliminates the need for special considerations for subjects with missing data. Although there is no perfect substitute for complete data, our approach provides a way to handle missing data using a straightforward application of well-known statistical methodology.
|Number of pages||11|
|Journal||Human biology; an international record of research|
|State||Published - Apr 1992|
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics