Clustered longitudinal data analysis
Extension and comparison of marginal models
Clustered longitudinal data are often collected as repeated measures on subjects arising in clusters. Examples include periodontal disease study, where the measurements related to the disease status of each tooth are collected over time for each patient which is considered as a cluster. For such applications, the number of teeth for each patient may be related to the overall oral health of the individual and hence may influence the distribution of the outcome measure of interest leading to an informative cluster size. Under such situations, three competing marginal linear models are proposed for clustered longitudinal data,namely, generalized…
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Produktdetails
- ISBN: 978-3-8383-1113-5
- EAN: 9783838311135
- Produktnummer: 37362996
- Verlag: LAP Lambert Academic Publishing
- Sprache: Englisch
- Erscheinungsjahr: 2010
- Seitenangabe: 68 S.
- Masse: H22.0 cm x B15.0 cm x D0.4 cm 119 g
- Abbildungen: Paperback
- Gewicht: 119
Über den Autor
Ming Wang is a PH.D student in the Department of Biostatistics and Bioinformatics at Emory University, Atlanta, GA, USA. Miss Wang received her Master degree in Biostatistics from the University of Louisville in August, 2008. Her primary research interest focuses on longitudinal data analysis, generalized linear model and survival analysis.
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