01896nas a2200289   4500000000100000008004100001260001600042653001300058653002900071653003700100653001100137653002300148653001200171653001800183653002500201653002500226653004200251653001300293100002100306700001200327700001300339245006800352300001200420490000700432520115300439022001401592       2005                            d  c2005 Apr 3010aBiometry10aClinical Trials as Topic10aData Interpretation, Statistical10aHumans10aLeprostatic Agents10aleprosy10aLinear Models10aLongitudinal studies10aMycobacterium leprae10aRandomized Controlled Trials as Topic10aRifampin1 aChandrasekaran V1 aGopal G1 aThomas A00aSummarizing data through a piecewise linear growth curve model.  a1139-510 v243 a<p>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 scientifically. Recent advances in statistical theory and software development incorporate the covariance structures such as unstructured, compound symmetry, auto-regressive and random effects, 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 fixed 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 different covariance structures, the linear model is fitted for Leprosy data and the residual sum of squares computed. Goodness of fit 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 fit, simulation studies are carried out and the results presented.</p>  a0277-6715