Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 639124, 13 pages
http://dx.doi.org/10.1155/2012/639124
Research Article

Let Continuous Outcome Variables Remain Continuous

Enayatollah Bakhshi,1 Brian McArdle,2 Kazem Mohammad,3 Behjat Seifi,4 and Akbar Biglarian1

1Department of Statistics and Computer, University of Social Welfare and Rehabilitation Sciences, Tehran 1985713834, Iran
2Department of Statistics, The University of Auckland, Private Bag 92010, Auckland, New Zealand
3Department of Biostatistics, School of Public Health and Institute of Public Health Research, Tehran University of Medical Sciences, Tehran, Iran
4Department of Physiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

Received 8 November 2011; Revised 21 February 2012; Accepted 29 February 2012

Academic Editor: Alberto Guillén

Copyright © 2012 Enayatollah Bakhshi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The complementary log-log is an alternative to logistic model. In many areas of research, the outcome data are continuous. We aim to provide a procedure that allows the researcher to estimate the coefficients of the complementary log-log model without dichotomizing and without loss of information. We show that the sample size required for a specific power of the proposed approach is substantially smaller than the dichotomizing method. We find that estimators derived from proposed method are consistently more efficient than dichotomizing method. To illustrate the use of proposed method, we employ the data arising from the NHSI.