A generalization of the growth curve model which allows missing data |
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Authors: | David G Kleinbaum |
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Institution: | Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27514 USA |
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Abstract: | This study presents methods for estimating and testing hypotheses about linear functions of the unknown parameters in a generalization of the growth curve model which allows missing data. The estimators proposed are best asymptotically normal (BAN). A testing method for large samples is described which uses a test criterion given in general form by Wald. The asymptotic null distribution of the test statistic is a central chi-square variable. A BAN estimator of a linear vector function of the unknown parameters of the expectation model and consistent estimators of the variance-covariance parameters are required for computation. |
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Keywords: | 62H05 62H15 Growth curves missing data hypothesis testing generalized model |
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