A reference text in the area of biostatistics (medical statistics). It discusses fully parametric models for discrete repeated measures data. It explores statistical models for time-dependent predictors where there may be feedback between the predictor and response variables. Series: Oxford Statistical Science Series. Num Pages: 398 pages, numerous tables and figures. BIC Classification: GPH; JHBC; MBNS; PBT. Category: (P) Professional & Vocational. Dimension: 240 x 159 x 26. Weight in Grams: 766. . 2002. 2nd Edition. hardcover. . . . .

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Bibliographic Details

Title: Analysis of Longitudinal Data: 25 (Oxford Statistical Science Series)
Publisher: OUP Oxford
Publication Date: 2002
Language: English
ISBN 10: 0198524846
ISBN 13: 9780198524847
Binding: Hardcover
Edition: 2nd Edition
Condition: New

About this title

Synopsis

The new edition of this important text has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving and important area of biostatistics. Two new chapters have been added on fully parametric models for discrete repeated measures data and on statistical models for time-dependent predictors where there may be feedback between the predictor and response variables. It also contains the many useful features of the previous edition such as, design issues, exploratory methods of analysis, linear models for continuous data, and models and methods for handling data and missing values.

About the Author

Peter Diggle is in the Department of Mathematics and Statistics, University of Lancaster. Patrick Heagerty is in the Biostatistics Department, University of Washington. Kung-Yee Liang and Scott Zeger are both in the Biostatistics Department, Johns Hopkins University.

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