Testing Hypotheses for the Growth Curve Model when the Data are Incomplete

James D. Leeper; Robert F. Woolson

doi:10.1080/00949658208810573

Testing Hypotheses for the Growth Curve Model when the Data are Incomplete

James D. Leeper, Robert F. Woolson

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Abstract

Kleinbaum (1973) developed a generalized growth curve model for analyzing incomplete longitudinal data. In this paper the small sample properties of several related test statistics are investigated via Monte Carlo techniques. The covariance matrix is estimated by each of three non-iterative methods. The null and non-null distributions of these test statistics are examined.

Original language	English
Pages (from-to)	97-107
Number of pages	11
Journal	Journal of Statistical Computation and Simulation
Volume	15
Issue number	2-3
DOIs	https://doi.org/10.1080/00949658208810573
State	Published - Aug 1982

Keywords

Growth curve analysis
Wald statistics
incomplete data

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10.1080/00949658208810573

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title = "Testing Hypotheses for the Growth Curve Model when the Data are Incomplete",

abstract = "Kleinbaum (1973) developed a generalized growth curve model for analyzing incomplete longitudinal data. In this paper the small sample properties of several related test statistics are investigated via Monte Carlo techniques. The covariance matrix is estimated by each of three non-iterative methods. The null and non-null distributions of these test statistics are examined.",

keywords = "Growth curve analysis, Wald statistics, incomplete data",

author = "Leeper, {James D.} and Woolson, {Robert F.}",

note = "Funding Information: Thi, work wai carried out while rhe first author waa a doctoral student at the Unirsrd!, of Iowa. It was partially supported by United States Public Health Service Grant MH2-1189.",

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N2 - Kleinbaum (1973) developed a generalized growth curve model for analyzing incomplete longitudinal data. In this paper the small sample properties of several related test statistics are investigated via Monte Carlo techniques. The covariance matrix is estimated by each of three non-iterative methods. The null and non-null distributions of these test statistics are examined.

AB - Kleinbaum (1973) developed a generalized growth curve model for analyzing incomplete longitudinal data. In this paper the small sample properties of several related test statistics are investigated via Monte Carlo techniques. The covariance matrix is estimated by each of three non-iterative methods. The null and non-null distributions of these test statistics are examined.

KW - Growth curve analysis

KW - Wald statistics

KW - incomplete data

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M3 - Article

AN - SCOPUS:0342558088

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SN - 0094-9655

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ER -

Testing Hypotheses for the Growth Curve Model when the Data are Incomplete

Abstract

Keywords

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