Summarizing data through a piecewise linear growth curve model

Chandrasekaran, V and Gopal, G and Thomas, A (2005) Summarizing data through a piecewise linear growth curve model. Statistics in Medicine, 24 (8). pp. 1139-1151. ISSN Print: 0277-6715; Online: 1097-0258

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Abstract

Most of the research in clinical trials is based on longitudinal designs, which involve repeated measurements of a variable of interest. Such designs are very powerful, both statistically and scienti�cally. Recent advances in statistical theory and software development incorporate the covariance structures such as unstructured, compound symmetry, auto-regressive and random e�ects, etc., for analysing longitudinal data. Hathaway et al. propose a technique for summarizing longitudinal data using linear growth curve model and establish that the number of summary statistics is �xed as four irrespective of the length of study. In this paper, we develop a procedure for analysing the longitudinal data through a piecewise linear growth curve model on the lines of Hathaway et al. Under di�erent covariance structures, the linear model is �tted for Leprosy data and the residual sum of squares computed. Goodness of �t has also been considered for various models. In order to prove that the proposed method is robust and better than the others in terms of goodness of �t, simulation studies are carried out and the results presented.

Item Type:	Article
Subjects:	Tuberculosis > Biostatistics
Divisions:	Statistics
Depositing User:	Dr. Rathinasabapati R
Date Deposited:	26 Nov 2013 10:09
Last Modified:	09 Mar 2016 07:01
URI:	http://eprints.nirt.res.in/id/eprint/690

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