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Main Title Analyzing Repeated Measurements with Possibly Missing Observations by Modelling Marginal Distributions.
Author Wei, L. J. ; Stram., D. O. ;
CORP Author Michigan Univ., Ann Arbor. Dept. of Biostatistics. ;Radiation Effects Research Foundation, Hiroshima (Japan).;Health Effects Research Lab., Research Triangle Park, NC.
Publisher c1988
Year Published 1988
Report Number EPA-R-813495; EPA/600/J-88/523;
Stock Number PB90-232299
Additional Subjects Biostatistics ; Mathematical models ; Biomathematics ; Statistical analysis ; Statistical distributions ; Reprints ; Health statistics
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NTIS  PB90-232299 Some EPA libraries have a fiche copy filed under the call number shown. 07/26/2022
Collation 12p
Abstract Suppose that subjects are observed repeatedly over a common set of time points with possibly time-dependent covariates and possibly missing observations. At each time point, the authors model the marginal distribution of the response variable and the effect of the covariates on that distribution using a class of quasi-likelihood models. No parametric model of dependence of the repeated observations of the subject is assumed. For large samples, the quasi-likelihood estimates of the time-specific regression coefficients over the set of predetermined time points are shown to be approximately jointly normal. This, coupled with various inference procedures, provides a global picture about the effects of the covariates on the response variable over the entire study period. A lack-of-fit test for testing the adequacy of the assumed quasi-likelihood model is also provided. All the methods considered are illustrated with real-life examples. (Copyright (c) 1988 by John Wiley & Sons, Ltd.)
Supplementary Notes Pub. in Statistics in Medicine, v7 p139-148 Feb 88. Prepared in cooperation with Radiation Effects Research Foundation, Hiroshima (Japan). Sponsored by Health Effects Research Lab., Research Triangle Park, NC.
NTIS Title Notes Journal article.
Title Annotations Reprint: Analyzing Repeated Measurements with Possibly Missing Observations by Modelling Marginal Distributions.
Category Codes 57U; 72F
NTIS Prices PC A03/MF A01
Primary Description 600/10
Document Type NT
Cataloging Source NTIS/MT
Control Number 022221267
Origin NTIS
Type CAT