Fitting growth curve models to longitudinal data with missing observations.

W. D. Johnson; V. T. George; A. Shahane; G. J. Fuchs

Fitting growth curve models to longitudinal data with missing observations.

W. D. Johnson, V. T. George, A. Shahane, G. J. Fuchs

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English (US)
Pages (from-to)	243-253
Number of pages	11
Journal	Human biology; an international record of research
Volume	64
Issue number	2
State	Published - Apr 1992
Externally published	Yes

ASJC Scopus subject areas

Ecology, Evolution, Behavior and Systematics
Genetics
Genetics(clinical)

Cite this

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title = "Fitting growth curve models to longitudinal data with missing observations.",

abstract = "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.",

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AB - 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.

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Fitting growth curve models to longitudinal data with missing observations.

Abstract

ASJC Scopus subject areas

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